PI positions

The School of Electrical Engineering at Aalto University invites applications for a position at the Assistant, Associate, or Full Professor level in the field of Learning and Intelligent Systems. We are looking for scientists with an outstanding research track record in AI/machine learning and dedication to applying it in intelligent systems. 

Applicants must demonstrate excellent research potential (for Assistant) and merits (for Associate and Full levels) in addition to teaching ability. This professorship is sought to specifically strengthen research excellence while also contributing to teaching in the school in the area of intelligent systems. The position will be placed in one of the departments of the school, best fitting the chosen candidate’s profile. We warmly welcome applicants from underrepresented groups.

The position has a competitive salary as well as a considerable start-up package. The contract includes occupational health benefits. Relocation services are also available for people coming from abroad. 

Requirements and Process 

Candidates applying in this call are asked to specify the level they are applying to. Applicants are required to have a doctoral degree in electrical engineering, computer science or a related field and expertise in both AI/machine learning and an application discipline relevant to us. The School of Electrical Engineering conducts research in, for example, circuit design, control engineering, human-computer interaction, neuromorphic computing, robotics and autonomous systems, signal processing, speech and acoustics, and communication engineering. We expect a strong publication record, including publications in top-tier conferences and/or journals, to demonstrate the candidate’s contributions and expertise. 

The applicants will be reviewed based on their research achievements in relation to their career stage, their ability to teach, and activity in the scientific community; recommendation letters will also be taken into consideration. Short-listed applicants will be invited to present and discuss their research with faculty. Evaluation at the Assistant Professor level is mainly based on research merits as well as the applicant’s potential. A person at any level of the tenure track system is expected to perform world‐class research; to teach, advise, and otherwise advance both graduate and undergraduate education; to be an active member of the international scientific community; and to exhibit academic leadership. Career advances on the tenure track are based on scheduled performance assessments, which take into account the candidate’s merits in all these areas.

An excellent command of both written and spoken English is required for teaching. We support the learning of local language (Finnish/Swedish) according to applicant’s own wishes. 

Further Information

Please contact the faculty search chair Professor Ville Kyrki or in recruitment process related questions HR Partner Julia Majuri; emails firstname.lastname@aalto.fi.

• School of Electrical Engineering: https://www.aalto.fi/en/school-of-electrical-engineering
• Aalto University: https://www.aalto.fi/en
• Living in Finland and working at Aalto https://www.aalto.fi/en/careers-at-aalto/for-international-staff

We are looking for a full, associate, or assistant professor (tenure track) of machine learning. The position offers a unique opportunity to engage in groundbreaking research and collaborations on a global scale within the expanding field of machine learning methodologies and solutions. 

The professorship strengthens Department of Computational Engineering's expertise in statistical learning methods for artificial intelligence with impact on basic research and society. The duties include the supervision of researchers and doctoral students as well as advanced education in topics related to computational sciences. 

You will work in a cutting-edge, interdisciplinary research environment in a diverse academic setting, fostering collaboration across multiple disciplines. You will be part of LUT's international community and networks, which enable global partnerships and expose you to different cultures and perspectives. You will have great possibilities for career growth and development. 

You will enjoy Finland’s high quality of life and benefit from the excellent local health care, social services, and a clean and safe environment. 

Your objective will be to set up your own research group and offer expertise in the field of your professorship. 

Your duties will include basic and advanced education in the professorship’s key areas; the specific educational responsibilities will be agreed on with the head of the degree programme. Professors are expected to supervise theses and doctoral dissertations. 

We expect proof of high-impact international research and publishing – the most important duties of professors at LUT University. 

Skills for collaborating both within LUT and with national and especially international partners are crucial to the position, and you will be expected to provide evidence of successful international collaboration and the acquisition of research funding. Preparations for national and especially international research and education projects are part of the work of professors at LUT University. 

The duties of a professor also include societal engagement that serves industry, the economy, and society, and general administrative work related to the university's operation. 

The field of the professorship can include themes such as the following: - machine learning-enhanced computational engineering 

• mathematical foundations of machine learning 

• hybrid/surrogate models 

• physics-informed machine learning or neural networks 

• statistical learning 

• explainable machine learning 

• applications in engineering, natural sciences, or high-performance computing 

Expertise in multiple areas listed above is considered an advantage. You must present proof of successful project work and research collaboration with research institutions and industry. In addition, we require evidence of experience in managing an organisation and acquiring competitive funding.

The duties related to the field of research include the following: 

• high-impact international research 

• planning and implementation of bachelor’s, master’s, and doctoral education - supervision of final theses and doctoral studies 

• preparation of national and international research and education projects - increasing awareness in a way that serves industries and society 

• taking part in the preparation of projects in other LUT units as an expert - general administrative work related to the university's operation 

• acquisition of research funding 

• cost-conscious leadership and project management 

• close collaboration and interaction with businesses in the field 

• teamwork, as most of the research and work is conducted in research groups and teams 

The position is at the assistant, associate, or full professor level of the tenure track and will be filled through an open call for a fixed term of four years (assistant/associate professor) or permanently (full professor). The tenure track system offers researchers a possibility to advance to a full professorship. LUT is committed to providing tenure track researchers the possibility to advance to the next level, provided they meet the requirements in the promotion reviews, are suitable for the position, and conduct research that fits LUT's strategy and operation. 

More information on the LUT tenure track system: 

https://www.lut.fi/en/research/research-career-lut/tenure-track 

The position starts with a six-month trial period and is based in either Lappeenranta or Lahti. The primary location will be negotiated with the superior. 

Additional information 

Further information on the duties of the professor is provided by Satu-Pia Reinikainen, head of the department, tel. +358 40 353 9039, satu-pia.reinikainen@lut.fi

We are looking for Professors in Fundamental Machine Learning at all tenure track levels (Assistant Professor, Associate Professor, and Professor) that are driven by excellence in research and teaching as well as have a strong interest for tangible theoretical contributions and addressing societal challenges. The successful candidate  conducts high-quality research on the studying and developing machine learning (ML) methods, related for example to robust ML, causal ML, interpretable ML, algorithmic  foundations of ML, physics-informed ML, multi- and cross-modal ML, natural language processing, reinforcement learning, geometric ML, graph learning, or ML for time series,  human-computer interaction, without excluding other relevant topics. 

Requirements and Process  

Applicants are expected to hold a doctoral degree in computer science or a closely related field and to have an established record of publications in machine learning, including publications in top-tier conferences and/or journals that reflect recognized expertise and impact in the field. 

At all tenure track levels, the position requires conducting internationally competitive research, contributing to undergraduate and graduate education through teaching and  supervision, active participation in the global research community, and demonstration of academic leadership. 

Candidates must qualify for ELLIS Scholar or Fellow status, depending on their academic age. Criteria can be found on the ELLIS website. Note that candidates must  conduct research in the field of machine learning, typically publishing in top tier venues in machine learning-driven fields. In exceptional cases, the ELLIS recruitment  committee may accept a very promising early-career researcher to an institute PI  position as a “rising star”, even if the candidate does not yet fully meet the ELLIS  Scholar criteria but is clearly on track to do so; within three years, the person must fulfill  the Scholar criteria. 

The institute has its own external committee for the evaluation (ELLIS recruitment  committee), nominated by the ELLIS Society' s Board, which independently evaluates  the candidates shortlisted by the universities. 

Further requirements for each tenure track level are as follows:  

Assistant Professor 

• applicable doctoral degree, 

• ability to undertake independent scholarly activity and potential to pursue scholarly activity at a high international level of excellence,

• teaching skills required to successfully perform the duties and functions of the  position. 

Associate Professor 

• applicable doctoral degree, 

• track record of international scholarly activity and potential to pursue scholarly activity at a high international level of excellence, 

• teaching skills required to successfully perform the duties and functions of the position, 

• ability to lead a research group and acquire external funding. 

Professor 

• applicable doctoral degree, 

• track record of scholarly activity at a high international level of excellence, 

• experience of leading scientific research, 

• ability to provide high-quality research-based education and instruction, 

• track record of winning external research funding. 

Evaluation will consider research accomplishments in relation to career stage, teaching  experience, and engagement in the scientific community. Recommendation letters will  also form part of the assessment. Selected candidates will be invited to present and discuss their research with the faculty. 

Initial appointment for assistant professor and for associate professor is for five years. Subject to successful performance, you will become a tenured member of the faculty  staff at the end of the first five-year period. Full professors will hold a permanent appointment from the outset. A trial period of six months applies to all our new  employees. Candidates may be invited for a video interview during the first stage of the  recruitment process. The most qualified candidates will be invited to Tampere  University for an interview and may undergo an aptitude assessment. They may also undergo a review by external experts and may be required to give a demonstration of  their teaching skills. 

Further information 

Further information on the position and the working environment may be obtained from:  Professor Alexandros Iosifidis (alexandros.iosifidis@tuni.fi) and about the tenure track career path: HR Specialist Safija Chabbi (safija.chabbi@tuni.fi) 

Faculty of Information Technology and Communication Sciences | Tampere universities

Information on Tampere University Tenure Track career path

We are looking for Professors in Applied Machine Learning at all tenure track levels  (Assistant Professor, Associate Professor, and Professor) that are driven by excellence in  research and teaching as well as have a strong interest for innovation and addressing  societal challenges. Within the Faculty of Information Technology and Communication  Sciences, there is expertise in several fields that are highly relevant to ML, including  computer vision, time-series modeling, audio, robotics, recommender systems, natural  language processing and text analysis, data-driven decision making, financial data  science, complex systems, human-computer interaction, human-centered AI, network  and information security, software engineering, AI in media, journalism, linguistics,  performing arts, extended reality, gamification, and games. We are looking for  applicants to strengthen and expand the research in the above topics, but topics  beyond the current research topics relevant to Applied Machine Learning are also  welcome. 

Requirements and Process 

Applicants are expected to hold a doctoral degree in computer science or a closely  related field and to have an established record of publications in machine learning,  including publications in top-tier conferences and/or journals that reflect recognized  expertise and impact in the field. 

At all tenure track levels, the position requires conducting internationally competitive  research, contributing to undergraduate and graduate education through teaching and  supervision, active participation in the global research community, and demonstration  of academic leadership. 

Candidates must qualify for ELLIS Scholar or Fellow status, depending on their  academic age. Criteria can be found on the ELLIS website. Note that candidates must  conduct research in the field of machine learning, typically publishing in top tier venues  in machine learning-driven fields. In exceptional cases, the ELLIS recruitment  committee may accept a very promising early-career researcher to an institute PI  position as a “rising star”, even if the candidate does not yet fully meet the ELLIS  Scholar criteria but is clearly on track to do so; within three years, the person must fulfill  the Scholar criteria. 

The institute has its own external committee for the evaluation (ELLIS recruitment  committee), nominated by the ELLIS Society' s Board, which independently evaluates  the candidates shortlisted by the universities. 

Further requirements for each tenure track level are as follows:  

Assistant Professor 

• applicable doctoral degree, 

• ability to undertake independent scholarly activity and potential to pursue  scholarly activity at a high international level of excellence,

• teaching skills required to successfully perform the duties and functions of the  position. 

Associate Professor 

• applicable doctoral degree, 

• track record of international scholarly activity and potential to pursue scholarly activity at a high international level of excellence, 

• teaching skills required to successfully perform the duties and functions of the  position, 

• ability to lead a research group and acquire external funding. 

Professor 

• applicable doctoral degree, 

• track record of scholarly activity at a high international level of excellence, 

• experience of leading scientific research, 

• ability to provide high-quality research-based education and instruction, 

• track record of winning external research funding. 

Evaluation will consider research accomplishments in relation to career stage, teaching  experience, and engagement in the scientific community. Recommendation letters will  also form part of the assessment. Selected candidates will be invited to present and discuss their research with the faculty. 

Initial appointment for assistant professor and for associate professor is for five years. Subject to successful performance, you will become a tenured member of the faculty  staff at the end of the first five-year period. Full professors will hold a permanent appointment from the outset. A trial period of six months applies to all our new  employees. Candidates may be invited for a video interview during the first stage of the recruitment process. The most qualified candidates will be invited to Tampere  University for an interview and may undergo an aptitude assessment. They may also  undergo a review by external experts and may be required to give a demonstration of  their teaching skills. 

Further information 

Further information on the position and the working environment may be obtained from:  Professor Juho Kanniainen (juho.kanniainen@tuni.fi) and about the tenure track career path: HR Specialist Safija Chabbi (safija.chabbi@tuni.fi)

Faculty of Information Technology and Communication Sciences | Tampere universities

Information on Tampere University Tenure Track career path

We are looking for Professors at all tenure track levels (Assistant Professor, Associate  Professor, and Professor), focusing on Machine Learning in Wireless Networks,  Positioning and Sensing. Successful candidates are to be driven by excellence in research and teaching as well as have a strong interest for innovation and addressing  societal challenges. Within the Faculty of Information Technology and Communication  Sciences, there is expertise in several fields that are highly relevant to ML, including 6G  and beyond mobile communication networks, radar and other sensing and situational awareness systems, wireless and multisensor localization systems, integrated sensing  and communications, network optimization and management, space and other aerial systems, and defense systems. We are looking for applicants to strengthen and expand  the research in the above topics, with particularly emphasis on Machine Learning, while complementary research thrusts beyond the above listed themes are also valued and welcome. 

Requirements and Process 

Applicants are expected to hold a doctoral degree in computer science, electrical  engineering, or a closely related field and to have an established record of publications  in machine learning, including publications in top-tier conferences and/or journals that  reflect recognized expertise and impact in the field. 

At all tenure track levels, the position requires conducting internationally competitive research, contributing to undergraduate and graduate education through teaching and  supervision, active participation in the global research community, and demonstration  of academic leadership. 

Candidates must qualify for ELLIS Scholar or Fellow status, depending on their  academic age. Criteria can be found on the ELLIS website. Note that candidates must  conduct research in the field of machine learning, typically publishing in top tier venues in machine learning-driven fields. In exceptional cases, the ELLIS recruitment  committee may accept a very promising early-career researcher to an institute PI position as a “rising star”, even if the candidate does not yet fully meet the ELLIS  Scholar criteria but is clearly on track to do so; within three years, the person must fulfill  the Scholar criteria. 

The institute has its own external committee for the evaluation (ELLIS recruitment  committee), nominated by the ELLIS Society' s Board, which independently evaluates  the candidates shortlisted by the universities. 

Further requirements for each tenure track level are as follows:  

Assistant Professor 

• applicable doctoral degree, 

• ability to undertake independent scholarly activity and potential to pursue  scholarly activity at a high international level of excellence,

• teaching skills required to successfully perform the duties and functions of the position. 

Associate Professor 

• applicable doctoral degree, 

• track record of international scholarly activity and potential to pursue scholarly  activity at a high international level of excellence, 

• teaching skills required to successfully perform the duties and functions of the  position, 

• ability to lead a research group and acquire external funding. 

Professor 

• applicable doctoral degree, 

• track record of scholarly activity at a high international level of excellence, 

• experience of leading scientific research, 

• ability to provide high-quality research-based education and instruction, 

• track record of winning external research funding. 

Evaluation will consider research accomplishments in relation to career stage, teaching  experience, and engagement in the scientific community. Recommendation letters will  also form part of the assessment. Selected candidates will be invited to present and discuss their research with the faculty. 

Initial appointment for assistant professor and for associate professor is for five years.  Subject to successful performance, you will become a tenured member of the faculty  staff at the end of the first five-year period. Full professors will hold a permanent  appointment from the outset. A trial period of six months applies to all our new  employees. Candidates may be invited for a video interview during the first stage of the  recruitment process. The most qualified candidates will be invited to Tampere  University for an interview and may undergo an aptitude assessment. They may also  undergo a review by external experts and may be required to give a demonstration of  their teaching skills. 

Further information 

Further information on the position and the working environment may be obtained from: Head of Unit, Professor Mikko Valkama (mikko.valkama@tuni.fi) and about the tenure track career path: HR Specialist Safija Chabbi (safija.chabbi@tuni.fi) 

Faculty of Information Technology and Communication Sciences | Tampere universities Information on Tampere

Information on Tampere University Tenure Track career path

The Faculty of Engineering and Natural Sciences at Tampere University invites  applications for positions at all Professor levels (Assistant Professor, Associate  Professor, and Professor) in the field of Machine Learning (ML) and Artificial Intelligence  (AI) viewed through the lens of physics. We are looking for an outstanding scientist who  applies physics-based methodologies—such as statistical physics, dynamical systems  theory, and related areas—to advance understanding of or develop novel ML and AI  models. The research goals and applications may include deepening the theoretical  foundations of ML and AI, improving algorithmic robustness, uncovering emergent  behaviors in learning systems as well as modelling critical phenomena, optimizing  learning dynamics, and designing sustainable ML and AI architectures inspired by  physical principles. 

Requirements and Process 

Applicants are expected to hold a doctoral degree in physics or a related field and have  experience in research in academia in the respective field or fields.  

At all tenure track levels, the position requires conducting internationally competitive  research, contributing to undergraduate and graduate education through teaching and  supervision, active participation in the global research community, and demonstration  of academic leadership. 

Candidates must qualify for ELLIS Scholar or Fellow status, depending on their academic age. Criteria can be found on the ELLIS website. Note that candidates must  conduct research in the field of machine learning, typically publishing in top tier venues  in machine learning-driven fields. In exceptional cases, the ELLIS recruitment  committee may accept a very promising early-career researcher to an institute PI position as a “rising star”, even if the candidate does not yet fully meet the ELLIS  Scholar criteria but is clearly on track to do so; within three years, the person must fulfill  the Scholar criteria. 

The institute has its own external committee for the evaluation (ELLIS recruitment  committee), nominated by the ELLIS Society' s Board, which independently evaluates  the candidates shortlisted by the universities. 

Further requirements for each tenure track level are as follows:  

Assistant Professor  

• ability to undertake high-level scholarly activity and potential to establish an independent agenda of scholarly activity at international level of excellence, 

• teaching skills required to successfully perform the duties and functions of  the position. 

Associate Professor  

• track record of independent scholarly activity on a high international level, 

• teaching skills required to successfully perform the duties and functions of the position,  

• ability to lead a research group and acquire external funding. 

Professor  

• high-level scholarly expertise,  

• experience of leading scientific research activities, 

• ability to provide high-quality research-based education and instruction,  

• track record of winning external research funding,  

• track record of international scholarly activity. 

Evaluation will consider research accomplishments in relation to career stage, teaching  experience, and engagement in the scientific community. Recommendation letters will  also form part of the assessment. Selected candidates will be invited to present and discuss their research with the faculty. 

Initial appointment for Assistant Professor and for Associate Professor is for five years. Subject to successful performance, you will become a tenured member of the faculty  staff at the end of the first five-year period. Full Professors will hold a permanent  appointment from the outset. You will be well-supported throughout the five-year period  to ease transition to TAU. A trial period of six months applies to all our new employees. Candidates may be invited for a video interview during the first stage of the recruitment  process. The most qualified candidates will be invited to Tampere University for an  interview and may undergo an aptitude assessment. They will also undergo a review by  external experts and may be required to give a demonstration of their teaching skills.  

Further Information 

Further information on the position and the working environment may be obtained from:  Professor, Dean Martti Kauranen (martti.kauranen@tuni.fi), about subject-specific  inquiries: Professor Lasse Laurson (lasse.laurson@tuni.fi and about the tenure track career path: HR Specialist Safija Chabbi (safija.chabbi@tuni.fi)  

Faculty of Engineering and Natural Sciences | Tampere universities

Information on Tampere University Tenure Track career path

The Faculty of Medicine and Health Technology invites applications for a position at all  tenure track levels (Assistant Professor, Associate Professor, and Professor) in the field  of AI in Health. The position will be located in the TECH unit of the faculty. There is a  strong potential for AI-based advances, e.g., in multi-modal data analysis (ranging from  –omics to imaging and electronic health records) for decision support, in the  combination of mechanistic with data-driven approaches to better understand human  health, and in the optimization of healthcare system resources and processes. We are  now looking for an outstanding machine learning/AI scientist, who has published in top  tier venues in AI-related fields, to realise this potential, building further on a strong  research track record in multi-disciplinary research projects, in fields such as data  science for healthcare, (biomedical) signal- and/or image processing, computational  modelling, trustworthy AI/ML, computer science, or healthcare informatics.  

Requirements and Process 

Applicants are expected to hold a doctoral degree in an applicable field and have  experience in research in academia in the respective field or fields. You regularly  publish at top tier venues in AI-driven fields.  

At all tenure track levels, the position requires conducting internationally competitive  research, contributing to undergraduate and graduate education through teaching and  supervision, active participation in the global research community, and demonstration  of academic leadership. 

Candidates must qualify for ELLIS Scholar or Fellow status, depending on their  academic age. Criteria can be found on the ELLIS website. Note that candidates must  conduct research in the field of machine learning, typically publishing in top tier venues  in machine learning-driven fields. In exceptional cases, the ELLIS recruitment  committee may accept a very promising early-career researcher to an institute PI position as a “rising star”, even if the candidate does not yet fully meet the ELLIS  Scholar criteria but is clearly on track to do so; within three years, the person must fulfill  the Scholar criteria. 

The institute has its own external committee for the evaluation (ELLIS recruitment  committee), nominated by the ELLIS Society' s Board, which independently evaluates  the candidates shortlisted by the universities. 

Further requirements for each tenure track level are as follows:  

Assistant Professor  

• applicable doctoral degree, 

• ability to undertake independent scholarly activity and potential to pursue  scholarly activity at a high international level of excellence, 

• teaching skills required to successfully perform the duties and functions of the position. 

Associate Professor  

• applicable doctoral degree,  

• track record of independent scholarly activity and potential to pursue scholarly  activity at a high international level of excellence, 

• teaching skills required to successfully perform the duties and functions of the position,  

• ability to lead a research group and acquire external funding.  

Professor  

• applicable doctoral degree,  

• track record of international scholarly activity at a high international level of  excellence,  

• experience of leading scientific research,  

• ability to provide high-quality research-based education and instruction,  

• track record of winning external research funding.  

Evaluation will consider research accomplishments in relation to career stage, teaching experience, and engagement in the scientific community. Recommendation letters will  also form part of the assessment. Selected candidates will be invited to present and discuss their research with the faculty. 

Initial appointment for assistant professor and for associate professor is for five years.  Subject to successful performance, you will become a tenured member of the faculty  staff at the end of the first five-year period. Full professors will hold a permanent  appointment from the outset. A trial period of six months applies to all our new  employees. Candidates may be invited for a video interview during the first stage of the  recruitment process. The most qualified candidates will be invited to Tampere  University for an interview and may undergo an aptitude assessment. They may also  undergo a review by external experts and may be required to give a demonstration of  their teaching skills. 

Further information 

Further information on the position and the working environment may be obtained from:  Professor Mark van Gils, mark.vangils@tuni.fi, +358504066610 and about the tenure track career path: HR Specialist Safija Chabbi (safija.chabbi@tuni.fi) 

Faculty of Medicine and Health Technology | Tampere universities 

Information on Tampere University Tenure Track career path

The Faculty of Medicine and Health Technology invites applications for a position at all  tenure track levels (Assistant Professor, Associate Professor, and Professor) in the field  of AI/ML for Microphysiological Systems. The position will be in the TECH unit of the  faculty. One of the rapidly growing areas of multidisciplinary in vitro science is  microphysiological systems (MPS) (or body/organ-on-chip platforms) where machine  learning /AI is expected to be developed and utilized to improve the translational  prediction power of 3D human tissue models. We offer the broadest collaboration  network in Finland to obtain in silico, in vitro and in vivo data for joint research.  

We are looking for an outstanding machine learning/AI scientist who has published at  top tier venues in AI-driven fields. We seek applicants with a genuine interest in collaborating on MPS-related research and with proven experience in any of the MPS related fields. Identified fields include e.g.: Modelling and simulation of organ-on-chips,  MPS-related biomaterials, or 3D human tissue models; Machine learning methodology  to correlate 3D in vitro cell models to human diseases; Machine learning methodology  to the regulatory aspects of MPS; and Data driven development of MPS methods.  

Requirements and Process 

Applicants are expected to hold a doctoral degree in an applicable field and have  experience in research in academia in the respective field or fields. You regularly  publish at top tier venues in AI-driven fields.  

At all tenure track levels, the position requires conducting internationally competitive  research, contributing to undergraduate and graduate education through teaching and  supervision, active participation in the global research community, and demonstration  of academic leadership. 

Candidates must qualify for ELLIS Scholar or Fellow status, depending on their academic age. Criteria can be found on the ELLIS website. Note that candidates must  conduct research in the field of machine learning, typically publishing in top tier venues in machine learning-driven fields. In exceptional cases, the ELLIS recruitment  committee may accept a very promising early-career researcher to an institute PI  position as a “rising star”, even if the candidate does not yet fully meet the ELLIS  Scholar criteria but is clearly on track to do so; within three years, the person must fulfill the Scholar criteria. 

The institute has its own external committee for the evaluation (ELLIS recruitment committee), nominated by the ELLIS Society' s Board, which independently evaluates  the candidates shortlisted by the universities. 

Further requirements for each tenure track level are as follows:  

Assistant Professor  

• applicable doctoral degree,

• ability to undertake independent scholarly activity and potential to pursue  scholarly activity at a high international level of excellence, 

• teaching skills required to successfully perform the duties and functions of the position.  

Associate Professor  

• applicable doctoral degree,  

• track record of independent scholarly activity and potential to pursue scholarly activity at a high international level of excellence, 

• teaching skills required to successfully perform the duties and functions of the position,  

• ability to lead a research group and acquire external funding.  

Professor  

• applicable doctoral degree,  

• track record of international scholarly activity at a high international level of excellence,  

• experience of leading scientific research,  

• ability to provide high-quality research-based education and instruction,  

• track record of winning external research funding.  

Evaluation will consider research accomplishments in relation to career stage, teaching  experience, and engagement in the scientific community. Recommendation letters will  also form part of the assessment. Selected candidates will be invited to present and discuss their research with the faculty. 

Initial appointment for assistant professor and for associate professor is for five years.  Subject to successful performance, you will become a tenured member of the faculty  staff at the end of the first five-year period. Full professors will hold a permanent  appointment from the outset. A trial period of six months applies to all our new  employees. Candidates may be invited for a video interview during the first stage of the  recruitment process. The most qualified candidates will be invited to Tampere  University for an interview and may undergo an aptitude assessment. They may also  undergo a review by external experts and may be required to give a demonstration of  their teaching skills. 

Further information 

Further information on the position and the working environment may be obtained from:  Professor Pasi Kallio, pasi.kallio@tuni.fi, +358500525546 and about the tenure track  career path: HR Specialist Safija Chabbi (safija.chabbi@tuni.fi) 

Faculty of Medicine and Health Technology | Tampere universities 

Information on Tampere University Tenure Track career path

The University of the Arts Helsinki invites applications for Full Professor position in the field of Digital Art: Emphasis in AI and co-creativity. 

The ideal candidate will possess expertise in AI, including, but not limited to applications of core machine learning methods (e.g., generative models, deep learning, reinforcement learning, Bayesian inference etc.). The successful candidate will demonstrate excellence in applying and developing AI methods in arts, in music, performing arts, media arts or writing. Furthermore, the ideal candidate will be familiar with contemporary creative practice, aesthetics and production of digital artworks as communities of co-creation. 

The selected professor will work across three Academies of the University of Arts Helsinki (Sibelius Academy, Theatre Academy, Academy Fine Arts) and will support multidisciplinary art, innovation and technology research and education across the university. 

Requirements and process

The qualification requirements of the Professor in Digital Art include an applicable doctoral degree as well as good evidence of high-quality research and ability to provide teaching based on artistic activities and/or research, and experience in educational development. Capability to obtain competitive funding, domestic and international cooperation and networking skills, and ability to influence society is required.

The merits of applicants are assessed as a whole in relation to the job description. 

Uniarts Helsinki's language policy promotes happy multilingualism. The languages of instruction at Uniarts Helsinki are Finnish, Swedish and English. In this position, excellent English language skills are required.

Short-listed applicants will be invited to site visit to present and discuss their research with faculty. 

Further Information 

Please contact the Vice Rector for Research Ossi Naukkarinen or in recruitment process related questions HR Specialist Leena-Kaisa Paananen; emails firstname.lastname@uniarts.fi 

More information 

University of the Arts: https://www.uniarts.fi/en/

Living in Finland and working at Uniarts Helsinki: https://www.uniarts.fi/en/working-at-uniarts-helsinki/

The Faculty of Science, Forestry and Technology at the University of Eastern Finland invites applications for a position in the field of AI methods in Science and Engineering. We are looking for an excellent researcher with a strong research background and demonstrated ability for independent scientific work through publications and other evidence. The applicant's qualification in scientific research and strong motivation should be demonstrated as progressive development. The applicant is expected to have strong expertise either in developing ML methods or in applying advanced AI methods to address complex challenges in computer science, natural sciences and/or engineering. Research that uses interdisciplinary approaches with diverse conceptual and methodological perspectives is particularly encouraged.  We value the strengthening of the diversity of our community in our recruitment.

Requirements and Process

Applications are invited for all Tenure Track levels: Assistant Professor, Associate Professor and Professor. The Tenure Track career stages prior to a full professorship are Assistant Professor and Associate Professor, both of which are fixed-term positions of four (4) years. The specific criteria and goals for each term will be agreed upon with the appointed candidate during the preparation of the employment contract. Advancement to the next Tenure Track level (towards a professorship) requires meeting the criteria defined in the contract.

A person appointed to a permanent professorship or to a professorship of more than two years must be scientifically or artistically qualified, possess good teaching skills, and, where relevant, have practical familiarity with the field. An Assistant/Associate Professor in the tenure track must hold a suitable doctoral degree and demonstrate good teaching skills. In addition, the candidate must have the potential to meet the qualification requirements for a full professorship by the end of the tenure track term.

Applicants will be evaluated based on their scientific qualifications, ability to perform the duties, and suitability for the appropriate stage of the Tenure Track. A professorship requires high-level scientific competence, experience in leading research, and the ability to provide high-quality research-based teaching and supervise theses. Strong motivation and evidence of international networking are also essential.

The evaluation will emphasize an independent research record demonstrated through first-author or senior-author publications in leading journals, proven ability to secure research funding, and experience supervising students at all levels. Active engagement in national and international collaborations with diverse networks across disciplines and regions will be highly valued. At the professorial level, broader leadership contributions are expected, such as editorial roles, keynote presentations, and involvement in major research initiatives. Exceptional achievements, including recognition as a top researcher or awards for best papers, are particularly encouraged. Recommendation letters will be taken into consideration.

External expert evaluation will be used in recruitment. Short-listed applicants will be invited to present and discuss their research with the faculty. 

Please note, we welcome applications from candidates who can teach in English and/or Finnish. We provide strong support for international staff and a collaborative, English-friendly work environment.

Further Information

Please contact the Dean of the Faculty of Science, Forestry and Technology, Professor Kari Lehtinen or in recruitment process related questions Executive Head of Administration Arja Hirvonen; emails firstname.lastname@uef.fi.  

Faculty of Science, Forestry and Technology: https://www.uef.fi/en/faculty-of-science-forestry-and-technology 

University of Eastern Finland: https://www.uef.fi/en. 

The Faculty of Health Sciences at the University of Eastern Finland invites applications in the field of AI in health sciences. We are looking for an excellent, advanced researcher with a strong research background and demonstrated ability for independent scientific work through publications and other evidence. The applicant's qualification in scientific research and strong motivation should be demonstrated as progressive development. The applicant must have excellent track record in developing and applying AI methods for integrating diverse health-related data across modalities and sources. Research that uses interdisciplinary approaches with diverse conceptual and methodological perspectives is particularly encouraged.  We value the strengthening of the diversity of our community in our recruitment.

Requirements and Process

Applications are invited for all Tenure Track levels: Assistant Professor, Associate Professor and Professor. The Tenure Track career stages prior to a full professorship are Assistant Professor and Associate Professor, both of which are fixed-term positions of four (4) years. The specific criteria and goals for each term will be agreed upon with the appointed candidate during the preparation of the employment contract. Advancement to the next Tenure Track level (towards a professorship) requires meeting the criteria defined in the contract.

A person appointed to a permanent professorship or to a professorship of more than two years must be scientifically or artistically qualified, possess good teaching skills, and, where relevant, have practical familiarity with the field. An Assistant/Associate Professor in the tenure track must hold a suitable doctoral degree and demonstrate good teaching skills. In addition, the candidate must have the potential to meet the qualification requirements for a full professorship by the end of the tenure track term.

Applicants will be evaluated based on their scientific qualifications, ability to perform the duties, and suitability for the appropriate stage of the Tenure Track. A professorship requires high-level scientific competence, experience in leading research, and the ability to provide high-quality research-based teaching and supervise theses. Strong motivation and evidence of international networking are also essential.

The evaluation will emphasize an independent research record demonstrated through first-author or senior-author publications in leading journals, proven ability to secure research funding, and experience supervising students at all levels. Active engagement in national and international collaborations with diverse networks across disciplines and regions will be highly valued. At the professorial level, broader leadership contributions are expected, such as editorial roles, keynote presentations, and involvement in major research initiatives. Exceptional achievements, including recognition as a top researcher or awards for best papers, are particularly encouraged. Recommendation letters will be taken into consideration.

External expert evaluation will be used in recruitment. Short-listed applicants will be invited to present and discuss their research with the faculty. 

Please note, we welcome applications from candidates who can teach in English and/or Finnish. We provide strong support for international staff and a collaborative, English-friendly work environment.

Further Information

Please contact the Dean of the Faculty of Health Sciences, Professor Markus Forsberg or in recruitment process related questions Executive Head of Administration Hanna Ollikainen-Richards; emails firstname.lastname@uef.fi.  

Faculty of Health Sciences: https://www.uef.fi/en/faculty-of-health-sciences

University of Eastern Finland: https://www.uef.fi/en.

The Faculty of Medicine and the Institute for Molecular Medicine Finland (FIMM)/HiLIFE of the University of Helsinki invite applications for Full Professor or Assistant/Associate Professor in computational precision health, specifically in Artificial Intelligence / Machine Learning methods development and application in health. We are looking for qualified candidates to carry out research in precision health motivated machine learning, with a focus on:

• Foundation models for longitudinal electronic health record (EHR) data, and/or
• Novel methods for multimodal prediction of disease onset, treatment response and prognosis

 to support and complement our current activities in the area.

The University of Helsinki, Faculty of Medicine, FIMM and HiLIFE offer excellent research environments and collaborator potential in molecular and clinical medicine, population health and other disciplines across faculties, e.g., in computer science and social sciences. FIMM is hosting exceptional research projects combining population-level genomic and health register data resources, such as the FinnGen study, nationwide longitudinal health registry, iCAN flagship discovery platform and EHR data. The research is supported by hi-performance supercomputer LUMI and highly scalable cloud-based sensitive data analysis environments FIMM Sandbox and Finngen Sandbox, and cloud-based datalake at HUS university hospital.

The Faculty of Medicine promotes scientific research of a high standard and is responsible for providing research-based undergraduate and postgraduate education in medicine, dentistry, psychology and logopedics, as well as for the English-language Master’s Programme in Translational Medicine, Master’s Programme in Development of Health Care Services and provides also psychotherapist education. In addition to its teaching and research activities, the Faculty serves as a significant expert organisation in the healthcare sector and contributes to the discourse on ethics in the field. In terms of research, the Faculty aims for a place among the best medical faculties in the world, while consolidating and strengthening its status as a top-level institution of medical education. 

 Together with HUS Helsinki University Hospital and the Helsinki Institute of Life Science (HiLIFE), the Faculty of Medicine, University of Helsinki, constitutes the Academic Medical Center. This medical center has been very successful in international comparisons, ranking among the top 10 medical campuses in Europe and among the top 50 globally.   

University of Helsinki is one of the leading multidisciplinary research universities in Europe and ranks among the top 100 international universities in the world. Its 11 faculties provide excellent opportunities for inter-disciplinary collaboration in many fields. University of Helsinki welcomes applicants from a variety of genders, linguistic and cultural backgrounds, and minorities.

Requirements and Process 

The person to be chosen must have a strong scientific track record in machine learning evidenced by publications in top tier forums of the field. 

The successful applicant may be appointed to a permanent full professorship or a fixed-term assistant/ associate professorship (tenure track), depending on their qualifications and career stage. For more information on the career path and the tenure track model at the University of Helsinki, please see https://www.helsinki.fi/en/about-us/careers/academic-careers/tenure-track. 

Candidates must hold a doctoral degree in data science, statistics, bioinformatics, computer science or other relevant field. A full professor must also have high-level academic qualifications and experience in leading scientific research in data science and/or its application to health sciences. The professor must also be able to provide research-based teaching of high quality, supervise dissertations and theses as well as show evidence of international cooperation in the field. 

An assistant/associate professor must have demonstrated ability for independent scientific work as well as skills to teach the subjects related to their research. Furthermore, the successful candidate is expected to have competence and motivation for scientific career proven by scientific publications and other academic activities.

The new professor is expected to teach in the relevant degree programmes at the faculty of medicine (e.g., MSc in Translational Medicine or relevant doctoral programmes) and teaching can take place in English, Finnish, or Swedish.

The position has a competitive salary as well as a competitive start-up package. 

The University of Helsinki offers comprehensive services to its employees, including occupational health care and health insurance, sports facilities, and opportunities for professional development. The university provides support for internationally recruited employees and their family members with their transition to work and life in Finland. For more on the University of Helsinki as an employer, please see https://www.helsinki.fi/en/about-us/careers.

Further Information

Further information on the position and the working environment may be obtained from:

• About the position and the operational environment: Dean Johanna Arola (johanna.t.arola(at)helsinki.fi) and FIMM Director Samuli Ripatti (samuli.ripatti(at)helsinki.fi)
• About the tenure track model: HR Specialist Anna Leppäkoski (anna.leppakoski(at)helsinki.fi)

The University of Helsinki invites applications for an assistant, associate or full professorship in Reliable Communicative AI. The position is dedicated to research on robust interactive AI with a focus on deep learning for trustworthy language models. The work combines different modalities of language-based communication (text, speech, audiovisual) and includes aspects of efficiency and reliability across domains and languages. The focus of the position is on methodological work with data-driven approaches to language and/or speech technology within the framework of generative AI.

Research topics of interest include:

• Development of reliable interactive AI and AI-mediated communication
• Robust generative AI across domains and languages
• Efficiency and trustworthiness
• Explainable AI and ethical/societal aspects of AI development

The ideal candidate will be expected to lead impactful research on data-intensive AI and to collaborate with existing research groups at the university and within the ELLIS Institute to strengthen our overall profile in machine learning and conversational AI. The successful candidate should also demonstrate a commitment to high-quality teaching, mentoring, and curriculum development at both undergraduate and graduate levels. The duties include securing external funding, and building networks within the university, industry, and broader society.

In the faculty of Humanities, the position will be connected to the Language Technology research group (Helsinki-NLP) at the Department of Digital Humanities in the City Center Campus of the University of Helsinki. The department is an ideal home for the professorship. Its globally recognized research groups are already leveraging advanced machine learning techniques to tackle challenges in the humanities and social sciences. Key areas of expertise include global-leading work on efficient NLP and machine translation (Language Technology), natural and expressive synthetic speech (Phonetics), and ML-validated computational models of human cognition (Cognitive Science). This established research ecosystem provides a fertile ground for a new professor to immediately thrive, fostering innovation at the intersection of technology and human communication. The Faculty provides a large potential for future collaboration in diverse disciplines. 

There are strong connections to leading labs in machine learning through international projects such as OpenEuroLLM and collaborations with dynamic industrial partners such as Silo/AMD, NVIDIA and Hugging Face, making the environment an attractive workplace for top talents.

The start-up package will be negotiated during the recruitment process. The University of Helsinki offers comprehensive services to its employees, including occupational health care, sports facilities, and opportunities for professional development. The university provides support for internationally recruited employees and their family members with their transition to work and life in Finland. For more on the University of Helsinki as an employer, please read more on our website.

Qualification requirements

The successful applicant may be appointed as a full professor or to a tenure-track position at the assistant or associate professor level, depending on their qualifications and career stage. Further information on careers and the tenure track model at the University of Helsinki is available on our website.

A candidate selected for the post of professor must possess a doctoral degree, high-level of academic competence, experience in management of scientific research, evidence of international co-operation in their field of study, and the ability to provide high-quality teaching based on research and to supervise theses and dissertations. When assessing the merits of an applicant, scientific publications and other research outcomes with academic value, teaching experience and teacher training, ability to produce study materials, other teaching merits and a teaching demonstration as well as participation in doctoral training will be taken into account.

A person selected for the post of assistant or associate professor must possess an appropriate doctoral degree, ability to conduct independent scientific work and experience in management of scientific research. In addition, the person must have evidence of international co-operation in their field of study, and the ability to provide high-quality teaching based on research and to supervise theses and dissertations. When assessing the merits of the applicants, special emphasis will be put on academic potential and quality.

In addition, the professor, assistant and associate professor applicant’s activity in the operations of the scholarly community, success in obtaining external research funding, academic work abroad and international duties will also be taken into account.

Duties

The duties of the professor, associate and assistant professor include conducting and supervising scientific research, teaching – including supervising Master and PhD students, staying up-to-date with the most current scientific developments in the field, and participating in societal interaction and international cooperation in the field. The person to be chosen is expected to co-operate with other research groups, to form and lead their own research group and to obtain external research funding both domestically and internationally. In addition, the professors, associate and assistant professors will be actively involved in undergraduate and postgraduate education and their development and perform assigned administrative duties.

Decision process

The preparatory group appointed by the dean takes care of practical arrangements related to the selection process. The preparatory group obtains expert statements on the scholarly merit of the top applicants chosen through the pre-selection process. Statements concerning the qualifications and merits of persons applying for the post are requested from a minimum of two external experts.

The short-listed candidates are requested to give a public scientific presentation and a teaching demonstration, the teaching demonstration will be evaluated. The top-ranked applicants will be interviewed.

Further Information

Please contact Prof. Jörg Tiedemann (head of Helsinki-NLP) at jorg.tiedemann@helsinki.fi for further information about the position and HR Specialist Jenni Syväoja (jenni.syvaoja@helsinki.fi) with questions about the recruitment process.

The Faculty of Information Technology at the University of Jyväskylä invites applications for a Professor or Assistant/Associate Professor (Tenure Track) position in the field of Machine Learning. The position of an Assistant Professor is for a fixed term of three to five years, and the position of an Associate Professor is for a fixed term of five years (according to the tenure track model at the University of Jyväskylä). The aim of the Tenure Track -path is to progress to a permanent professorship. The Professor position is valid until further notice.  

We are looking for an outstanding scientist with clear evidence of high-impact international publishing in the field or a highly talented assistant / associate level candidate with a strong research track record. We are especially interested in candidates with research interest in AI method development satisfying special requirements of a domain related to the Faculty research, for example in: Software Engineering, Education, Human Technology or Cybersecurity. 

The research at the Faculty of Information Technology addresses a wide spectrum of IT areas from machine learning, decision-making, data analysis, cybersecurity, software engineering, and information system science to educational technology and cognitive science. The faculty’s 17 research groups address basic research problems and multidisciplinary research topics with researchers from diverse areas like physics and engineering to education science, management, wellbeing and sports.  

Requirements and Process  

Candidates applying are required to have a doctoral degree in computer science or a related field. The candidate is expected to demonstrate independent contributions and expertise in the field. The candidates are also expected to have excellent collaboration skills in multi-disciplinary settings and experience of international cooperation in the field. Proven ability to obtain external funding is regarded as a merit. 

The candidates will be reviewed based on their research achievements in relation to their career stage, pedagogical merits, societal impact, and activity in the scientific community. The recruited candidate is expected to perform world‐class research at any level of the tenure track system. Professor is expected to have experience in heading scientific research. At the Assistant Professor level the evaluation is mainly based on research merits and applicant’s future potential. 

The duties and qualification requirements of an Assistant/Associate Professor and Professor are stipulated by the University of Jyväskylä Regulations and language skills guidelines. The qualification requirements should be met before the closing time of this call. A trial period of six months will be used in the beginning of the employment.  

Benefits

Finland has a high standard of living, with free schooling (also in English), affordable childcare, good family benefits, and healthcare. Jyväskylä is located in central Finland in the Finnish lakeland and has excellent opportunities for different nature, outdoor, and sports activities. The city of Jyväskylä is a major educational center and the city has a large student population. As such there is a vibrant cultural scene in the city. To find useful information about the University of Jyväskylä, the City of Jyväskylä and living in Finland, see the University's International Staff Guide.

After signing the employment contract, a personal career plan is made for you. The career plan specifies the objectives, intermediate milestones and evaluation criteria of the tenure track period. Your personal career plan helps you clarify your goals, and you will receive regular feedback on your work in the initial and follow-up discussions. You have the opportunity to apply for the Rector’s start-up funding to support the initiation of your research. Application will be assessed and funding is granted on a discretionary basis, see more details on page. 

We will also support your progress through mentoring, training and other support activities needed. Career path progression is based on an overall assessment of a person's progress. If you are moving from abroad, we will support your move to Jyväskylä and Finland. With its location among the forests and lakes of Central Finland, Jyväskylä offers a safe environment to live and work. Finnish society offers many benefits to families with children, and as a researcher living in Jyväskylä you will be able to balance work and personal life.

Further information 

Further information on the position and the working environment may be obtained from: Dean Pasi Tyrväinen, pasi.tyrvainen@jyu.fi, +358405408646, Faculty of Information Technology at the University of Jyväskylä 

Further information about the tenure track model: HR Partner Elina Korhonen, elina.a.korhonen@jyu.fi 

The Department of Mathematics and Statistics, in the Faculty of Mathematics and Science at the University of Jyväskylä invites applications for an Assistant/Associate Professor (Tenure Track)position in Mathematics (Probability / Mathematical Foundations of Data Science). This position offers an exceptional opportunity to join a top-ranked department and its vibrant, international, and interdisciplinary research community on one of Finland's most beautiful campuses. The position of an Assistant Professor is for a fixed term of three to five years, and the position of an Associate Professor is for a fixed term of five years (according to the tenure track model at the University of Jyväskylä). The aim of the Tenure Track -path is to progress to a permanent professorship. 

We are looking for candidates with a research profile in probability (stochastics) and related fields. Areas of interest include, but are not limited to, pure and applied probability, mathematical foundations of statistics and data science, mathematical finance, and mathematical physics. In particular, we welcome applications from candidates with research profiles related to the mathematical theory of machine learning, complexity theory, and from candidates that strengthen the interactions between the research groups of the department. If a suitable candidate is found, the position may be filled as a PS Fellow position.

The main research areas in the department are mathematical analysis and geometry, probability theory, inverse problems, and statistics with their applications. The department is a member of the Finnish Centre of Excellence in Randomness and Structures, and The Flagship of Advanced Mathematics for Sensing, Imaging and Modelling, FAME.

The successful candidate will be expected to conduct high-impact research, secure external funding, teach at all academic levels (BSc, MSc, and PhD), supervise students, and collaborate with other research groups within the university.

Requirements and Process 

Candidates applying are required to have a doctoral degree in Mathematics, Statistics, Computer Science, or a closely related field. The candidates are expected to have a demonstrated ability for independent scientific research work, evidenced by high-quality publications. The candidates are also expected to have excellent collaboration skills and experience of international cooperation. We highly value experience in, and enthusiasm for, research-based teaching and thesis supervision. Potential or a proven track record in acquiring external research funding is considered a requirement for the position.

The candidates will be reviewed based on their research achievements in relation to their career stage, pedagogical merits, societal impact, and activity in the scientific community.

The duties and qualification requirements of an Assistant/Associate Professor are stipulated by the University of Jyväskylä Regulations and language skills guidelines. The qualification requirements should be met before the closing time of this call. A trial period of six months will be used in the beginning of the employment. 

Benefits

Finland has a high standard of living, with free schooling (also in English), affordable childcare, good family benefits, and healthcare. Jyväskylä is located in central Finland in the Finnish lakeland and has excellent opportunities for different nature, outdoor, and sports activities. The city of Jyväskylä is a major educational center and the city has a large student population. As such there is a vibrant cultural scene in the city. To find useful information about the University of Jyväskylä, the City of Jyväskylä and living in Finland, see the University's International Staff Guide.

After signing the employment contract, a personal career plan is made for you. The career plan specifies the objectives, intermediate milestones and evaluation criteria of the tenure track period. Your personal career plan helps you clarify your goals, and you will receive regular feedback on your work in the initial and follow-up discussions. You have the opportunity to apply for the Rector’s start-up funding to support the initiation of your research. Application will be assessed and funding is granted on a discretionary basis, see more details on page. 

We will also support your progress through mentoring, training, and other support activities needed. Career path progression is based on an overall assessment of a person's progress. If you are moving from abroad, we will support your move to Jyväskylä and Finland. With its location among the forests and lakes of Central Finland, Jyväskylä offers a safe environment to live and work. Finnish society offers many benefits to families with children, and as a researcher living in Jyväskylä you will be able to balance work and personal life.

Further information 

For further information on the position, please contact the Head of the Department, Prof. Tapio Rajala, tapio.m.rajala@jyu.fi, tel. +358 40 805 4593.

For further information about the tenure track model, please contact HR Partner Paula Sarkkinen, paula.t.sarkkinen@jyu.fi.

The Faculty of Information Technology and Electrical Engineering (ITEE) invites applications for a tenure-track position at the Assistant Professor level. Applicants will also be considered for PS Fellowships.  Outstanding candidates are welcome in all areas broadly related to AI. This covers a wide range from hardware to software to theoretical principles. Areas included, but not limited to, autonomy, human-AI interaction, decision support, algorithms, modelling, machine learning, massive-data management, hardware device layers, hardware computing layers, federated and decentralized machine learning for communication and networking, signal processing, computer vision, robotics, security, and ethics. 

The position includes a starting package to build your research group and relocation services for candidates coming from abroad. We welcome applicants from all backgrounds, including people of different ages, genders, and lingual, cultural, or minority groups.

Artificial intelligence is a strategic cornerstone of ITEE, covering core machine learning, human-AI interaction, robotics, and AI-native communication networks. Our existing strengths include multimodal and federated learning at the edge, trustworthy perception and interaction, semantic and AI-driven 5G/6G systems, and embodied intelligence that integrates algorithms, devices, and resilient local infrastructures. ITEE links world-class AI research with practical impact in education, healthcare, industry, and society, with strengths in distributed and reinforcement learning; AI-enhanced communication systems; robust architectures for autonomous systems; and transparent, human-AI cooperation. 

Requirements and Process 

This call is for Assistant Professor positions only. Our tenure-track Assistant Professor positions are positioned for exceptionally talented researchers with high potential to advance in their careers.  A candidate must perform world-class research, teach, advise, participate in graduate and undergraduate education, engage with the international scientific community, demonstrate academic leadership, and acquire competitive research funds. Most importantly, the candidate is expected to develop into an independent thought leader with global visibility and impact. 

Candidates are required to hold a doctoral degree in computer science, statistics, or a related field, granted no more than ten years ago, with a strong publication record in AI/ML-related venues, including top-tier conferences/journals (see the list of example venues required by ELLIS: https://ellis.eu/members/become-member).

The selection process follows the recruitment guidelines of the University of Oulu. Assistant Professor will be a tenure-track position with five-year terms at each level. For more information on the tenure-track system, career pathways, and recruitment at the University of Oulu, please refer to:

https://www.oulu.fi/en/university/careers/diverse-career-pathways/tenure-track

https://www.oulu.fi/en/university/careers/hr-excellence-research/open-transparent-and-merit-based-recruitment-university-oulu 

Further Information

For further information about the position and the operational environment, please contact: Professor Mehdi Bennis (mehdi.bennis@oulu.fi) or Professor Steven LaValle (steven.lavalle@oulu.fi). 

For further information about the recruitment process or general matters, please contact: HR Partner Ellinoora Blomqvist (ellinoora.blomqvist@oulu.fi).

More information

• Faculty of Information Technology and Electrical Engineering: https://www.oulu.fi/itee
• Working at the University of Oulu: https://www.oulu.fi/en/university/careers & https://www.oulu.fi/en/university/careers/working-university-oulu
• Benefits and wellbeing: https://www.oulu.fi/en/university/careers/staff-benefits & https://www.oulu.fi/en/university/careers/get-settled-services-for-employees
• Living in Oulu: https://www.oulu.fi/en/university/careers/living-oulu

The Faculty of Information Technology and Electrical Engineering (ITEE) invites applications for all Professor levels. Applicants will also be considered for PS Fellowships. Outstanding candidates working in the fields of machine learning and AI are welcome to apply. Research areas of interest include, but are not limited to, machine learning algorithms, computer vision, natural language processing, multimodal data analysis, medical or biomedical image and signal analysis, robotics, and data security. 

The position includes a starting package to build your research group and relocation services for candidates coming from abroad. We welcome applicants from all backgrounds, including people of different ages, genders, and lingual, cultural, or minority groups.

Artificial intelligence is a strategic cornerstone of ITEE. Work at ITEE spans core machine learning, multimodal perception, computer vision, signal and biomedical data analysis, human-AI interaction, robotics, and bio-inspired autonomous systems. Research themes include robust and trustworthy perception; multimodal and federated learning at the edge; adaptive and context-aware AI for cyber-physical and autonomous systems; and embodied intelligence that integrates sensing, control, and learning in real-world environments. These strengths support impactful applications in healthcare, industry, energy, and society, such as medical imaging and diagnostics, intelligent automation, and emotion-aware interaction.

Requirements and Process 

Our Assistant and Associate Professor (tenure-track) positions are positioned for exceptionally talented researchers with high potential to advance in their careers. The Professor position is targeted for experienced and highly qualified candidates who have already advanced in their careers. A selected candidate is expected to perform world-class research, teach, advise, participate in graduate and undergraduate education, engage with the international scientific community, demonstrate academic leadership, and acquire competitive research funds. The candidates will be reviewed based on their research achievements in relation to their career stage.

Candidates are required to hold a doctoral degree in computer science, statistics, or a related field (for Assistant Professor, the doctoral degree should not have been granted more than ten years ago). The candidate should also have a strong publication record in AI/ML-related venues, including top-tier conferences/journals (see the list of example venues required by ELLIS: https://ellis.eu/members/become-member).

The selection process follows the recruitment guidelines of the University of Oulu. Assistant or Associate Professor level will be tenure-track positions with five-year terms at each level. The Professor position will be a permanent, tenured position. For more information on the tenure-track system, career pathways, and recruitment at the University of Oulu, please refer to:

https://www.oulu.fi/en/university/careers/diverse-career-pathways/tenure-track

https://www.oulu.fi/en/university/careers/hr-excellence-research/open-transparent-and-merit-based-recruitment-university-oulu 

Further Information

For further information about the position and the operational environment, please contact: Professor Janne Heikkilä (janne.heikkila@oulu.fi) or Adjunct Professor Satu Tamminen (satu.tamminen@oulu.fi), or Professor Juha Röning (Juha.Roning@oulu.fi)

For further information about the recruitment process or general matters, please contact: HR Partner Ellinoora Blomqvist (ellinoora.blomqvist@oulu.fi).

More information

• Faculty of Information Technology and Electrical Engineering, https://www.oulu.fi/itee
• Working at the University of Oulu: https://www.oulu.fi/en/university/careers & https://www.oulu.fi/en/university/careers/working-university-oulu
• Benefits and wellbeing: https://www.oulu.fi/en/university/careers/staff-benefits & https://www.oulu.fi/en/university/careers/get-settled-services-for-employees
• Living in Oulu: https://www.oulu.fi/en/university/careers/living-oulu

The Faculty of Medicine invites applications for all Professor levels in the field of health AI. The position will be located in the Research Unit of Health Sciences and Technology (HST). HST Unit is a multidisciplinary research unit having innovative experts in multimodal medical imaging, including clinical sciences (radiology, radiotherapy, clinical neurophysiology, physiatry), biomedical engineering, medical physics, medical informatics, biomarkers, and health sciences (nursing science and health administration science). A central part of the strategy is Digital Health and related technology applications. HST unit enables a nationally unique opportunity to combine health sciences with technological innovations.

We are now looking for an outstanding scientist with a strong track record in developing fundamental machine learning methodologies for health applications. The position includes a starting package to build your research group and relocation services for candidates coming from abroad.  We welcome applicants from all backgrounds, including people of different ages, genders, and lingual, cultural, or minority groups.

Requirements and Process 

Our Assistant and Associate Professor (tenure-track) positions are targeted for exceptionally talented researchers with high potential to advance in their careers. The Professor position is targeted for experienced and highly qualified candidates who have already advanced in their careers. A selected candidate is expected to perform world-class research, teach, advise, participate in graduate and undergraduate education, engage with the international scientific community, demonstrate academic leadership, and acquire competitive research funds. The candidates will be reviewed based on their research achievements in relation to their career stage.

Candidates are required to hold a doctoral degree in a machine learning related field (for Assistant Professor, the doctoral degree should not have been granted more than ten years ago). The candidate should also have a strong publication record in AI/ML-related venues, including top-tier conferences/journals (see the list of example venues required by ELLIS: https://ellis.eu/members/become-member). 

The selection process follows the recruitment guidelines of the University of Oulu. Assistant or Associate Professor level will be tenure-track positions with five-year terms at each level. The Professor position will be a permanent, tenured position. For more information on the tenure-track system, career pathways, and recruitment at the University of Oulu, please refer to:

https://www.oulu.fi/en/university/careers/diverse-career-pathways/tenure-track

https://www.oulu.fi/en/university/careers/hr-excellence-research/open-transparent-and-merit-based-recruitment-university-oulu 

Further Information

For further information about the position and the operational environment, please contact: Professor Simo Saarakkala (simo.saarakkala@oulu.fi) 

For further information about the recruitment process or general matters, please contact: HR Partner Ellinoora Blomqvist (ellinoora.blomqvist@oulu.fi).

More information

• Faculty of Medicine: https://www.oulu.fi/en/university/faculties-and-units/faculty-medicine
• Working at the University of Oulu: https://www.oulu.fi/en/university/careers & https://www.oulu.fi/en/university/careers/working-university-oulu
• Benefits and wellbeing: https://www.oulu.fi/en/university/careers/staff-benefits & https://www.oulu.fi/en/university/careers/get-settled-services-for-employees
• Living in Oulu: https://www.oulu.fi/en/university/careers/living-oulu

The University of Turku invites applications for a Professor (full) or tenure-track position (Assistant or Associate Professor) in Embodied Artificial Intelligence. We seek candidates in the field of machine learning, who work on the design, development, and understanding of intelligent systems that interact with the physical and social world. Potential areas of focus include, but are not limited to, sensorimotor control, developmental robotics, cognitive architectures, human-robot interaction, consciousness modeling, and adaptive, lifelong learning in physical agents. These examples are not exhaustive, and other relevant research topics are welcome. 

Candidates will be evaluated based on their scientific excellence, methodological novelty, and capacity to establish the collaborations necessary within the University. The position will be hosted by the Faculty of Technology. 

In addition to strong research credentials, we value broad academic, professional, and societal networks, an active commitment to societal impact, outreach, and technology transfer, as well as industrial and entrepreneurial experience and multidisciplinary collaboration. The successful candidate should also demonstrate a commitment to high-quality teaching, mentoring, and curriculum development at both undergraduate and graduate levels, with enthusiasm for educational development, teaching experience, and pedagogical studies. 

The start-up package will be negotiated during the recruitment process. The contract includes occupational health benefits. Relocation services are also available for people coming from abroad.  

Detailed qualification requirements, duties and process 

Further Information 

Please contact Prof. Juha Plosila  juplos@utu.fi (Department of Computing) or Prof. Jaakko Järvi jaakko.jarvi@utu.fi (Dean of Faculty of Technology) with questions about the position, and Ms. Sanna Hirvola sanna.hirvola@utu.fi (Head of Faculty Administration, Faculty of Technology) with questions about the recruitment process. 

More information 
●       Faculty of Technology 
●       Welcome to the University of Turku, relocation guide

The University of Turku invites applications for a Professor (full) or tenure-track position (Assistant or Associate Professor) in Artificial Intelligence in Human-Computer Interaction. With the increasingly more capable AI agents, the interaction between humans and computers will become more conversational and multi-modal: AI agents will interpret end users’ intentions, validate the correctness of the interpretation with the user, and then execute the action to satisfy the user’s intent. We are seeking experts whose research agenda is to find solutions within this newly emerged research area that falls between machine learning and software engineering. 

Candidates will be evaluated based on their scientific excellence, methodological novelty, and capacity to establish the collaborations necessary within the University. The position will be hosted by the Faculty of Technology. 

In addition to strong research credentials, we value broad academic, professional, and societal networks, an active commitment to societal impact, outreach, and technology transfer, as well as industrial and entrepreneurial experience and multidisciplinary collaboration. The successful candidate should also demonstrate a commitment to high-quality teaching, mentoring, and curriculum development at both undergraduate and graduate levels, with enthusiasm for educational development, teaching experience, and pedagogical studies. 

The start-up package will be negotiated during the recruitment process. The contract includes occupational health benefits. Relocation services are also available for people coming from abroad.  

Detailed qualification requirements, duties and process 

Further Information 

Please contact Prof. Ville Leppänen ville.leppanen@utu.fi (Department of Computing) or Prof. Jaakko Järvi  jaakko.jarvi@utu.fi (Dean of Faculty of Technology) with questions about the position, and Ms. Sanna Hirvola sanna.hirvola@utu.fi (Head of Faculty Administration, Faculty of Technology) with questions about the recruitment process. 

More information 
●       Faculty of Technology 
●       Welcome to the University of Turku, relocation guide

The University of Turku invites applications for a Professor (full) or tenure-track position (Assistant or Associate Professor) in Machine Learning in Quantum Sciences. The successful candidate is expected to build a teaching and research program on the use of machine learning in quantum sciences as well as quantum machine learning. The topic includes the use of quantum computing combined with machine learning for solving physical problems but is not limited to it. 

We look for candidates that can build synergies with the existing quantum physics research on open quantum systems, quantum networks, ultracold atomic gases and complex systems at the Department of Physics and Astronomy. Broader collaboration with other research clusters such as space physics and materials research at the Faculty of Science is encouraged. 

Access to supercomputers as well as hybrid classical-quantum computers and (in future) small-scale quantum computers can be provided by Centre for Scientific Computing (CSC) in Finland. University of Turku has an active environment also in AI research in general and hosts already two ELLIS Principal Investigators (large language models, machine learning in medical diagnosis).

Candidates will be evaluated based on their scientific excellence, methodological novelty, and capacity to establish the collaborations necessary within the University. The position will be hosted by the Department of Physics and Astronomy at the Faculty of Science.

In addition to strong research credentials, we value broad academic, professional, and societal networks, an active commitment to societal impact, outreach, and technology transfer, as well as industrial and entrepreneurial experience and multidisciplinary collaboration. The successful candidate should also demonstrate a commitment to high-quality teaching, mentoring, and curriculum development at both undergraduate and graduate levels, with enthusiasm for educational development, teaching experience, and pedagogical studies.

The start-up package will be negotiated during the recruitment process. The contract includes occupational health benefits. Relocation services are also available for people coming from abroad. 

→ Detailed qualification requirements, duties and process

Further Information

Please contact Prof. Kalle-Antti Suominen (Head of Laboratory of Quantum Optics) kalle-antti.suominen@utu.fi or Prof. Jyrki Piilo (Head of Laboratory of Theoretical Physics) jyrki.piilo@utu.fi with questions about the position, and Ms. Merja Fehlig merja.fehlig@utu.fi (Head of Administration, Faculty of Science) with questions about the recruitment process.

The School of Technology and Innovations at University of Vaasa provides internationally recognized engineering and business education and research. The School’s research strengths include computer vision, artificial intelligence methods, positioning technologies and systems, distributed automation systems, smart grids, quality and technology management, logistics, blockchain technology and flexible energy resources. The position supports the implementation of the University of Vaasa strategy 2030: Sustainable Business, Energy and Society and especially the ‘Energy Transition and Technology’ focus area. 

The Cyber-Physical Systems (CPS) Research Group is seeking applications for a tenure-track Professor position in Artificial Intelligence (AI) and Machine Learning (ML). This position offers an exciting opportunity to contribute to research and innovation in the intersection of AI, ML, and CPS, with a particular emphasis on applications in energy transition technology. 

The selected candidate will be expected to conduct high-impact research, develop innovative AI/ML methodologies, and apply these approaches to the development of intelligent cyber-physical systems. Special consideration will be given to candidates whose work addresses:

• Data -driven solutions for energy transition, including renewable energy optimization, smart grids, and energy-efficient industrial processes.
• Integration of AI/ML with technology focusing on autonomous systems, telecommunications, and smart environments.
• Advancements in CPS, including edge intelligence, real-time decision-making for example in robotics, and human-CPS interaction.

The position will also involve teaching and mentoring at the undergraduate and graduate levels, fostering interdisciplinary collaboration, and securing external research funding.

The position will be filled as a fixed-term Assistant Professor or Associate Professor or permanent Professor position under the tenure track system.

Scope and task definition

The core philosophy underlying the multidisciplinary approach of the Cyber-Physical Systems (CPS) research team is grounded in the crucial role that data plays as the primary interface between the physical and cyber realms. In today’s interconnected world, data is generated from a diverse array of sources, including sensors, Internet of Things (IoT) devices, social networks, cameras, databases, markets, and even environmental factors like weather patterns that impact renewable energy sources. This vast and ever-expanding pool of data serves as the fundamental building block for bridging the gap between the tangible, real-world systems and their digital counterparts.

As the volume, complexity, and variety of this data continue to grow, Artificial Intelligence (AI) and Machine Learning (ML) have become indispensable tools for effectively processing and analyzing it. By leveraging advanced algorithms, AI and ML are able to extract meaningful insights from raw data, uncover hidden patterns, and make predictions with unprecedented accuracy. This process not only enables the creation of innovative services but also enhances the functionality and performance of existing systems, driving improvements in efficiency, reliability, and resilience.

Candidates should demonstrate expertise in the following areas (not necessarily all):

• A PhD in Mathematics (Statistics), Computer Science, Electrical Engineering, or a closely related field.
• A strong research record with publications relevant to the position. Applicants should have a substantial number of publications in top-tier conferences and journals.
• Solid mathematical foundations in machine learning algorithms, including probabilistic methods, linear algebra, and optimization techniques.
• Familiarity with various machine learning algorithms, particularly deep learning, reinforcement learning, and transformers.
• Experience in applying AI and ML to big data, preferably in the areas of energy transition, automation, or smart systems.
• Proficiency in developing AI/ML models for complex, real-world cyber-physical systems (CPS) applications.
• Ability to teach and supervise students effectively in AI/ML and related subjects.
• A proven track record (or strong potential) in securing research funding and fostering industry collaboration.

For further detailed information about the requirements, criteria and our Tenure track procedure, please see: www.uwasa.fi/en/tenure-track

Further information

Raine Hermans, Dean, School of Technology and Innovations, tel. +358 29 449 8622, email: raine.hermans(a)uwasa.fi

Mohammed Elmusrati, Professor, School of Technology and Innovations, tel. +358 29 449 8275, email: mohammed.elmusrati(a)uwasa.fi 

Åbo Akademi University invites applications for a Professor or Associate Professor in Artificial Intelligence. The position is part of the Information Technology unit at the Faculty of Science and Engineering, work can be conducted in Turku or Vaasa.

We are looking for a machine learning, or more generally artificial intelligence researcher, with experience in one or several of the following areas:

• Data driven green transition
• Embodied AI (social/humanoid robotics, agents, etc.)
• High performance, energy efficient and low emission algorithms and computer platforms
• Mission critical, secure and resilient software systems
• Modeling and simulation

Work on applications in the bioscience, maritime, and manufacturing industry are an asset.

In this role you will contribute to the research and education provided in our unit, supervise doctoral researchers, and acquire and manage externally funded research projects in collaboration with other academic or industrial partners. The position has a competitive salary, including occupational health-care benefits, as well as a competitive start-up package to build your research group: https://www.ellisinstitute.fi/PI-recruit#1-what-we-offer

Depending on your experience, you can be appointed as professor or associate professor. Employment as professor concerns permanent employment. Employment as associate professor is within the tenure track career system, meaning a fixed term contract aimed towards a full professorship and permanent employment.

More information about the research within the unit is available in the research portal of ÅAU: https://research.abo.fi/en/organisations/information-technology-common

Requirements and Process 

In addition to a doctoral degree, a professor is required to possess solid scientific competence along with the ability to provide qualitative, research-based instruction and supervision, the ability to lead research projects and raise funding for research, experience in international research, and collaborative and leadership skills. An associate professor (level 2) is required to hold a doctoral degree as well as to possess solid experience in research, the potential to lead research groups and raise funding for research, and experience in international research. Moreover, teaching skills are required.

For teaching and research positions at Åbo Akademi University, excellent proficiency in Swedish and the ability to understand Finnish are required. Foreigners and non-native Finnish citizens are exempted from this requirement. In this case, the person appointed is expected to acquire or improve their language skills in Swedish during the employment period.

The applicants will be reviewed based on their research achievements in relation to their career stage, their teaching merits and activity in the scientific community; recommendation letters will also be taken into consideration. In weighing the applicant’s competence, scientific competence accounts for 50%, pedagogical competence for 25% and leadership and collaboration for 25% of the evaluation. Short-listed applicants will be invited to interviews and to present and discuss their research. More information about the position and the qualification and evaluation criteria can be found in the appointment plan.

Further Information

Please contact Professor Ivan Porres for questions concerning the position or HR Specialist Anna Lübchow for questions concerning the recruitment process; emails firstname.lastname@abo.fi.

• Åbo Akademi University: https://www.abo.fi/en
• Information Technology unit at Åbo Akademi University :https://www.abo.fi/en/information-technology-research-and-researchers
• Working at Åbo Akademi University https://www.abo.fi/en/about-abo-akademi-university/come-work-with-us/