PI positions

Applicants must be early-career and demonstrate excellent research potential in addition to teaching ability. This assistant professorship position is sought to specifically strengthen research excellence while also contributing to teaching in our department in the area of machine learning. If a suitable candidate is found, the position may be filled as a PS Fellow position.

Our department is committed to fostering an inclusive environment with diverse faculty members. We are the first department in Finland with a Vice-Head specifically focusing on diversity. The position has a competitive salary as well as a competitive start-up package. The contract includes occupational health benefits. Relocation services are also available for people coming from abroad. 

Requirements and Process 

Candidates applying to this call are considered for Assistant Professor positions only. Applicants are required to have a doctoral degree in computer science or a related field and a publication track record in machine learning, typically including publications in top-tier conferences and/or journals, demonstrating the candidate’s contributions and expertise in the field. Those candidates who have not received their doctoral degrees yet are expected to obtain the degree no later than August 31, 2025. Applicants with more than seven years of research experience after their doctoral degree (excluding relevant career breaks) are not considered early-career and should look for more advanced positions.

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. Short-listed applicants will be invited to present and discuss their research with faculty. Evaluation at the Assistant Professor level follows the tenure track system at Aalto University and 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.

Please observe that we welcome applications from candidates who can teach in English, Finnish or Swedish.

Further Information

Please contact the faculty search chair Professor Samuel Kaski or in recruitment process related questions HR Partner Laura Kuusisto-Noponen; emails firstname.lastname@aalto.fi.

• Department of Computer Science
  https://www.aalto.fi/en/department-of-computer-science
• 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

The Department of Information and Service Management at Aalto University invites applications for a tenure-track Assistant Professorship in Information Systems Science.

Qualifications: Prospective candidates must have a Ph.D. in a core business discipline such as Information Systems, or a Ph.D. in Computer Science, Data Science, or Computer Engineering, with research focused on problems related to the development, management, methods, decision-making or optimization and applications of AI and ML in business.

Department and Programs: The Department of Information and Service Management consists of three disciplinary areas: Information Systems Science, Logistics, and Management Science. The department offers bachelor’s and master’s programs in Information and Service Management and Business Analytics. The Department values an active approach to international research collaboration and business cooperation, supported by our current faculty and Aalto's multidisciplinary collaboration platforms for research and education.

Expectations: Qualified applicants should have an interest in interdisciplinary and collaborative research. Publications in leading IS outlets are expected and publications in AI conferences such as NeurIPS and ICML, or AI journals, are appreciated, although not required. Successful candidates are expected to have hands-on experience with both research and teaching involving machine learning or AI in business settings. The ability to teach and supervise students with diverse backgrounds, both business-oriented and technically inclined, is essential. Relevant professional (industry) work experience is a bonus.

Application Review: Applicants will be reviewed based on their research achievements relative to their career stage, teaching merits, and activity in the scientific community. Recommendation letters will also be considered. Short-listed applicants will be invited to present and discuss their research with faculty.

Evaluation at the Assistant Professor level follows the tenure track system at Aalto University and is primarily based on research merits and the applicant’s potential. Tenure-track faculty are expected to perform world-class research, teach, advise, and otherwise advance both graduate and undergraduate education, be active members of the international scientific community, and exhibit academic leadership. Career advances on the tenure track are based on scheduled performance assessments that consider the candidate’s merits in all these areas.

Further Information: Please contact the search committee chair Professor Matti Rossi or in recruitment process related questions HR Partner Heli Solla; emails firstname.lastname@aalto.fi.

The School of Electrical Engineering at Aalto University invites applications for positions at the Assistant, Associate, and Full Professor levels in the field of 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 wireless communications. 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 welcome applications from candidates who can teach in English, and in Finnish or Swedish.

Further Information

Please contact the faculty search chair Professor Ville Kyrki or in recruitment process related questions HR Partner Karoliina Walldén; 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

Department of Chemistry and Materials Science at Aalto University invites applications for tenure-track Assistant Professor position in the field of Machine Learning in Materials Science. 

We are looking for outstanding candidates with deep expertise in machine learning and ability to utilize machine learning approaches in pioneering materials research. Your research focuses on challenging material systems and phenomena such as interfaces, phase boundaries and dislocations, amorphous and disorganized materials, adaptive materials, or nanoscale devices. The studied materials could be applied for example in energy conversion and storage, microelectronics, sensors, or optoelectronics. A unique competitive edge of Aalto University and Finland in the field of machine learning and artificial intelligence research is LUMI, one of the most powerful supercomputers in the world. 

Requirements and Process

A doctoral degree in materials science, chemistry, physics, computational sciences, applied mathematics, or in a related field is a prerequisite for the position. Potential candidates possess a high-level publication track record in the development and application of machine learning methods in materials research. We expect you to establish and lead an outstanding research program in machine-learning driven materials research. We value commitment to high-level teaching as the position includes teaching and supervision at the B.Sc., M.Sc., and doctoral levels. We are looking for candidates who can teach in English, Finnish, or Swedish. Proven ability to obtain competitive research funding, experience of researcher supervision, and industrial collaborations are considered as merits.

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. Shortlisted applicants will be invited to a site visit at Aalto. A person at any level of the Aalto 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.

Further information

Please contact the faculty search chair Professor Kari Laasonen or in recruitment process related questions HR Partner Tiina Torvinen; emails firstname.lastname@aalto.fi.

• Department of Chemistry and Materials Science: https://cmat.aalto.fi
• Aalto University: https://www.aalto.fi/en
• Living in Finland: https://www.aalto.fi/en/careers-at-aalto/for-international-staff

The Department of Chemical and Metallurgical Engineering at Aalto University invites applications for tenure-track positions at the Assistant level in the field of Artificial Intelligence / Machine Learning for Chemical Process Automation. 

We are looking for outstanding candidates with proven track record in the development and application of state-of-the-art machine-learning methods for the simulation, control and automation of chemical processes. You should be able to build data-driven models that predict outcomes, recognize operational patterns, and improve processes across their value chain. Developing and using digital twins allows studying processes during extreme conditions helping to improve existing design and control practices towards autonomy. A unique competitive edge of Aalto University and Finland in the field of machine learning and artificial intelligence research is LUMI, one of the most powerful supercomputers in the world. 

Requirements and Process 

A Doctoral degree in process engineering, chemical engineering, systems engineering, applied mathematics, computer science or another related field is a prerequisite for the position. We are looking for a publication track record in the development and application of machine learning methods related to process engineering. We expect you to establish a high-level research group in machine-learning driven process analytics and decision-making. We value commitment to high-level teaching as the position includes teaching and supervision at the Bachelor, Master’s, and Doctoral levels. We are looking for candidates who can teach in English, Finnish, or Swedish. Proven ability to obtain external funding, experience of researcher supervision, and industrial collaborations are considered as merits.

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. Shortlisted applicants will be invited to a site visit at Aalto. A person at any level of the Aalto 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.

Further Information

Please contact the faculty search chair Professor Rodrigo Serna or in recruitment process related questions HR Partner Alice Björklund; emails firstname.lastname@aalto.fi.

• Department of Chemical and Metallurgical Engineering: https://www.aalto.fi/en/department-of-chemical-and-metallurgical-engineering
• Aalto University: https://www.aalto.fi/en
• Living in Finland: https://www.aalto.fi/en/careers-at-aalto/for-international-staff

Hanken School of Economics is one of the leading business schools in the Nordic countries. It is located in Finland, with campuses in Helsinki and Vaasa. Hanken offers a range of B.Sc., M.Sc., EMBA, PhD, and Executive Development programmes taught mainly in English and Swedish. Hanken has 2 725 Bachelor and Master’s students, and 118 Doctoral students. The School has close ties to the business community and an active alumni network with over 13 800 alumni working in more than 70 countries. The School is accredited by AACSB, AMBA, and EQUIS. The mission of Hanken is to create new knowledge and educate responsible professionals for the global economy and changing society. The Master’s programme was ranked 57 in the Masters in Management by Financial Times in 2024. Hanken is also recognized for its research quality, its international orientation, and its focus on sustainability. 

Hanken is looking to strengthen its research and teaching, particularly in business and Artificial Intelligence (AI), within the areas of finance, or marketing, or management and organisation. We are seeking an expert who will play an important role in achieving this goal. The tenure-track position in “AI and Business” is open to any level: professor, associate professor or assistant professor. If a suitable candidate is found, the position may be filled as a PS Fellow position. The position will be filled from August 1, 2025 (or as agreed). The position can be based at either of Hanken’s campuses, in Helsinki or Vaasa.

The role requires a doctoral degree. Fluency in English is required, knowledge of Swedish is considered a merit. Successful applicants should have existing and future research planned within AI and business, related to finance, or marketing, or management and organisation. Programming skills in relevant languages, experience with machine learning, or big data technologies are considered merits.  

When evaluating the applicants’ qualifications for an assistant professor position, the focus will be on the ability or potential to conduct independent high-quality research with original ideas and impact; and the ability or potential to independently provide high-quality teaching. 

Applicants for the Associate and Full Professor levels are expected to have demonstrated an internationally high level of scientific research quality within the scientific field of the position, high level of teaching quality, and to have made contributions through institutional service and societal impact. 

Faculty members are expected to carry out and supervise scientific research, provide high quality academic teaching, closely follow the advances of their field, and participate in service to Hanken, the academic community, and the society. 

The full-time position has an annual working time of 1612 hours. Hanken offers relocation support for tenure track professors coming from outside Finland and expects full-time academic employees to reside and work in Finland. During the academic year, it is expected that a minimum average of three days per week is spent on campus to actively contribute to the research and teaching environment. Teaching tasks are allocated based on the curriculum needs of the subject and by considering relevant own expertise. 

Salary

The salary is based on the university salary system in Finland (includes employee healthcare as well as pension and holiday contributions). The exact salary level depends on the recruited individual’s qualifications and performance. Hanken will support the selected employee with a start-up research budget, and additional research, travel and teaching development grants can also be applied for. Hanken rewards excellence in both research and teaching.

Interviews

Shortlisted candidates will be invited to on-site campus visits including an interview and a research presentation in Spring 2025. 

Associate and Full Professor appointments include external evaluations.

For more Information

For additional information, please contact Professor Benjamin Maury, benjamin.maury@hanken.fi or regarding the recruitment process HR Director Elina Stadigh, elina.stadigh@hanken.fi.

General instructions for applicants are provided here. Also, read more about Hanken as an employer here.

The Department of Computational Engineering (CopE) of LUT University invites applications for a tenure-track position in the field of Machine Learning. The position will be filled for a fixed term of four years (assistant / associate professor) or permanently (full professor).  We are looking for an outstanding scientist with a strong research track record. Proofs of high-impact international publishing in the field and acquisition of competitive external funding are valued. The professorship is a co-affiliation at LUT University, and ELLIS Institute Finland.

CopE's research is multidisciplinary and focuses on inverse problems, numerical analysis, computer vision and pattern recognition, atmospheric science and computational spectroscopy. Our cross-cutting theme is machine learning enhanced computational engineering, with interests in statistical learning, hybrid/surrogate models, physics/chemistry-informed machine learning, mathematical foundations, uncertainty quantification, computer vision, and pattern recognition. The professor position will enhance CopE's expertise in developing machine learning methods for AI, impacting both basic research and society. Duties include supervising researchers and doctoral students and providing advanced education in computational and data sciences.

Applicants will benefit from LUT's international community and networks that enable global partnerships and offer insights into different cultures and perspectives. We offer competitive salary, occupational health services and relocation services for people coming from abroad. The position is based in either Lappeenranta or Lahti, Finland.

Requirements and Process

Applicants are required to have a doctoral degree in computer science or a related field. The publication track record in machine learning is expected to focus on top-tier conferences and journals, demonstrating the candidate's individual contributions and expertise in the field.

The applicants will be reviewed based on their research achievements in relation to their career stage, teaching merits and activity in the scientific community; recommendation letters will be taken into consideration at the Assistant Professor level. Short-listed applicants are invited to an interview and to give a presentation of their research. Selection criteria follow the tenure track system at LUT University and are mainly based on research merits as well as the person's potential. A person at any level of the tenure track system is expected to perform world-class research, to teach and supervise graduate and post-graduate education, to be an active member of the international scientific community, and to show 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.

Further Information

For further information, please follow the links:

• Description of the appointment process
• LUT University
• Department of Computational Engineering
   

More information is provided by the following (firstname.lastname@lut.fi):

• Satu-Pia Reinikainen, Head of Computational Engineering Department, School of Engineering Sciences
• Toni Karvonen, Associate Professor in Applied Mathematics
• Lasse Lensu, Head of Computer Vision and Pattern Recognition Laboratory

The Faculty of Information Technology and Communication Sciences at Tampere University invites applications for positions at all Professor levels in the field of Electrical Engineering, especially in Communications and Networking. We are looking for outstanding scientists with a strong research track record in, for example, AI native 6G networks, semantic communications and machine learning, or Artificial Intelligence / Machine Learning for physical layer technology, radio resource management and mobility management, or wireless sensing and positioning. 

Requirements and Process 

Applications are welcomed to all tenure track levels (Assistant Professor, Associate Professor and Professor). You should have a doctoral degree in the field of communications engineering, networking, computer science, or a related field and have experience in research in academia in the respective field or fields. You regularly publish at top tier venues in related fields. 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
• teaching skills required to successfully perform the duties and functions of the position
• ability to lead a research group and acquire external funding
• track record of international scholarly activity. 

 Professor 

• applicable doctoral degree
• high-level international scholarly expertise
• experience of leading scientific research
• ability to provide high-quality research-based education and instruction
• track record of winning external research funding
• track record of international scholarly activity 

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. You will be well-supported throughout the five-year period to ease transition to faculty positions. 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 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, Vice-Dean for Research Juho Hamari, research.itc@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

The Faculty of Medicine and Health Technology invites applications for a position at assistant professor level 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 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 

Applications are welcomed for a tenure track position at Assistant Professor level. You should have a doctoral degree in the field of computer science/electrical engineering/data science/information technology or a related field with a strong additional knowledge of biomedical engineering or health technology, and have experience in research in academia in the respective field. You regularly publish at relevant top-tier venues. Furthermore, you have excellent collaboration skills in multi-disciplinary settings. 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.

Initial appointment for assistant 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.  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 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 Information Technology and Communication Sciences at Tampere University invites applications for positions at all Professor levels in Artificial Intelligence in media. The position will be situated either in Computing Sciences Unit, Communications Sciences Unit, or Languages Unit. We are looking for outstanding scientists with a strong research track record in AI, for example, in Multimedia (e.g. audio, video), Multimodality, , Journalism, Linguistics, Performing Arts, Extended Reality, Gamification, or Games.

Requirements and Process 

Applications are welcomed to all tenure track levels (Assistant Professor, Associate Professor and Professor). You should have 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 related fields. 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
• teaching skills required to successfully perform the duties and functions of the position
• ability to lead a research group and acquire external funding
• track record of international scholarly activity. 

 Professor 

• applicable doctoral degree
• high-level international scholarly expertise
• experience of leading scientific research
• ability to provide high-quality research-based education and instruction
• track record of winning external research funding
• track record of international scholarly activity 

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. You will be well-supported throughout the five-year period to ease transition to faculty positions. 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 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, Vice-Dean for Research Juho Hamari, research.itc@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

The Faculty of Information Technology and Communication Sciences at Tampere University invites applications for positions at all Professor levels in the across the field of Computer Sciences. We are looking for outstanding computing science scientists with a strong research track record in, for example, Computer Engineering, Human–Computer Interaction, Network and Information Security, Signal Processing, or Software Engineering, including human-centered AI foci such as AI ethics.

Requirements and Process 

Applications are welcomed to all tenure track levels (Assistant Professor, Associate Professor and Professor). You should have a doctoral degree in the field of computer science or a related field and have experience in research in academia in the respective field or fields. You regularly publish at top tier venues in related fields. 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
• teaching skills required to successfully perform the duties and functions of the position
• ability to lead a research group and acquire external funding
• track record of international scholarly activity. 

 Professor 

• applicable doctoral degree
• high-level international scholarly expertise
• experience of leading scientific research
• ability to provide high-quality research-based education and instruction
• track record of winning external research funding
• track record of international scholarly activity 

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. You will be well-supported throughout the five-year period to ease transition to faculty positions. 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 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, Vice-Dean for Research Juho Hamari, research.itc@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

The Faculty of Information Technology and Communication Sciences at Tampere University invites applications for positions at all Professor levels in the field of theoretical Machine Learning. We are looking for outstanding machine learning scientists with a strong research track record in fields such as theoretical foundations of Machine Learning, computational learning theory, model training and optimization, efficient, interpretable, trustworthy and scalable Machine Learning, and foundation models in Machine Learning (uni- and multi-model FMs, diffusion and generative models).

Requirements and Process 

Applications are welcomed to all tenure track levels (Assistant Professor, Associate Professor and Professor). You should have 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. 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
• teaching skills required to successfully perform the duties and functions of the position
• ability to lead a research group and acquire external funding
• track record of international scholarly activity. 

 Professor 

• applicable doctoral degree
• high-level international scholarly expertise
• experience of leading scientific research
• ability to provide high-quality research-based education and instruction
• track record of winning external research funding
• track record of international scholarly activity 

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 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, Vice-Dean for Research Juho Hamari, research.itc@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

The University of the Arts Helsinki invites applications for Full Professor position in the field of Digital Art: Emphasis in AI and co-creativity. If a suitable candidate is found, the position may be filled as a PS Fellow position.

The ideal candidate will possess expertise in AI, including, but not limited to affective computing, generative models, deep learning and ethical machine learning. The successful candidate will demonstrate excellence in applying and developing AI 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, versatile teaching skills and pedagogical experience, the ability to provide teaching based on artistic activities and/or research, and experience in educational development.

In addition, good evidence of the development and management of artistic or research and pedagogical activities, obtaining competitive funding, domestic and international cooperation and networking, and influencing 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 are Finnish, Swedish and English.

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 Teemu Leinonen or in recruitment process related questions HR Specialist Leena-Kaisa Paananen; emails firstname.lastname@uniarts.fi 

• 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 Department of Technical Physics at the University of Eastern Finland invites applications in the field of Computational engineering. If a suitable candidate is found, the position may be filled as a PS Fellow position. 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 expertise in applying AI methods together with advanced physical models to solving various engineering challenges. Research that uses interdisciplinary analytical 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

Applicants will be evaluated according to the qualifications required for the professorship and the qualifications required to perform the duties. According to the University Act, a professor must conduct and supervise scientific research or artistic work, provide teaching based on it, follow the development of science or art, and participate in societal interaction and international cooperation in their field.

The position of professor requires an applicable doctoral degree, high-level scientific competence, experience in leading scientific research, the ability to provide high-level research-based teaching, and to supervise theses. The position requires strong ability, motivation, and evidence of international networking and networks.

The evaluation will consider the applicant’s strong independent research background, as evidenced by first-author or senior-author publications in top-tier outlets. They must also have a proven ability to secure research funding and experience supervising students at various levels, including Bachelor's, Master's, and PhD students. A key consideration will be the candidate’s engagement in national and international collaborations, including the breadth and diversity of their networks across scientific disciplines, geographic regions, and academic backgrounds. Leadership roles such as editorial membership in reputable journals, keynotes, or contributions to scholarly books will also be highly valued. Researchers who demonstrate exceptional achievements, such as selection as top researchers or awards for best papers, are encouraged to apply. Recommendation letters will be taken into consideration.

Successful candidates are expected to conduct world-class research in applying AI methods to various fields of engineering, e.g. materials science, medical technology as well as different applications in chemistry and biology. In addition, responsibilities include teaching, supervising students, enhancing graduate and undergraduate education, participating in the international scientific community, and demonstrating academic leadership. Short-listed applicants will be invited to present and discuss their research with the faculty. Please note that we welcome applications from candidates who can teach in English and/or Finnish. Statements on the qualification and merits of the applicants for professorship shall be requested from external experts.

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.  

• Department of Technical Physics: https://www.uef.fi/en/unit/department-of-technical-physics 

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

The School of Computing at the University of Eastern Finland invites applications in the field of Precision XAI. If a suitable candidate is found, the position may be filled as a PS Fellow position. 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 expertise in the areas of Precision XAI/ML, which includes precision (idiographic or person-specific), within-person or person-centered research using XAI, ML, complex systems or intensive longitudinal data. Research that uses interdisciplinary analytical approaches with diverse conceptual, applied and methodological perspectives is particularly encouraged. We value the strengthening of the diversity of our community in our recruitment.

Requirements and Process

Applicants will be evaluated according to the qualifications required for the professorship and the qualifications required to perform the duties. According to the University Act, a professor must conduct and supervise scientific research or artistic work, provide teaching based on it, follow the development of science or art, and participate in societal interaction and international cooperation in their field.

The position of professor requires an applicable doctoral degree, high-level scientific competence, experience in leading scientific research, the ability to provide high-level research-based teaching, and to supervise theses. The position requires strong ability, motivation, and evidence of international networking and networks.

The evaluation will consider the applicant’s strong independent research background, as evidenced by first-author or single-author publications in top-tier outlets. They must also have a proven ability to secure research funding and experience supervising students at various levels, including Bachelor's, Master's, and PhD students. A key consideration will be the candidate’s engagement in national and international collaborations, including the breadth and diversity of their networks across scientific disciplines, geographic regions, and academic backgrounds. Leadership roles such as editorial membership in reputable journals, keynotes, or contributions to scholarly books will also be highly valued. Researchers who demonstrate exceptional achievements, such as selection as top researchers or awards for best papers, are encouraged to apply. Recommendation letters will be taken into consideration.

Successful candidates are expected to conduct world-class Precision XAI research, teach, supervise students, enhance graduate and undergraduate education, participate in the international scientific community, and demonstrate academic leadership. Short-listed applicants will be invited to present and discuss their research with the faculty. Please note that we welcome applications from candidates who can teach in English and/or Finnish. Statements on the qualification and merits of the applicants for professorship shall be requested from external experts.

Further Information

Please contact the Head of the School of Computing Professor Markku Tukiainen or in recruitment process related questions Executive Head of Administration Arja Hirvonen; emails firstname.lastname@uef.fi. 

• School of Computing: https://www.uef.fi/en/unit/school-of-computing

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

The Department of Computer Science at the Faculty of Science of the University of Helsinki invites applications for Full Professor or Assistant/Associate Professor in computer science, specifically in Artificial Intelligence / Machine Learning. If a suitable candidate is found, the position may be filled as a PS Fellow position. We are looking for qualified candidates to carry out research in machine learning to support and complement our current activities (see e.g. https://www.helsinki.fi/en/researchgroups/probabilistic-machine-learning) in the area.

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 University of Helsinki, Faculty of Science, and the Department of Computer Science offer excellent collaborator potential both in computer science and other disciplines across different faculties, e.g., in medicine, law, and social sciences. The Faculty of Science offers excellent computational infrastructure, including Hile, a small-scale replica of EuroHPC Lumi to facilitate development and deployment of computation on Lumi.

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 computer science or other relevant field. A full professor must also have high-level academic qualifications and experience in heading scientific research. 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 (e.g., MSc in Data Science or MSc in Computer Science) 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: Professor Jussi Kangasharju (jussi.kangasharju(at)helsinki.fi) (https://www.cs.helsinki.fi/)
• About the tenure track model: HR Specialist Jussi Hartikainen (jussi.a.hartikainen(at)helsinki.fi) 

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 explainable AI, AI methods for decision making, or machine learning methods satisfying special requirements of a domain related to the Faculty research, for example, cybersecurity or learning design.

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 14 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. 

We are offering competitive salary and substantial starting package to build your research group. We have also JYU's starting grant for new tenure track -professors enables a smooth start. The start-up funding is up to 60 000 euros. Applications will be assessed taking into account the need for start-up funding to ensure the effective launch of the research activity, which must be justified in the application, see JYU´s starting grant.  

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 Faculty of Law at the University of Lapland invites applications for one Tenure Track position open at all the 3 levels in the field of Law and AI. If a suitable candidate is found, the position may be filled as a PS Fellow position.

The Faculty of Law has a vibrant community of researchers working on a variety of legal issues, but increasingly focusing on key research streams, namely law and justice in different areas of society linked to socio-techno-environmental change.  

For at least 30 years, the Faculty of Law has focused on research on law and technology in the broadest sense, addressing issues arising from how law reacts to and provokes technological developments. This has been done in different research groups that have evolved over the years - from the group anchored in the Institute for Law and Informatics, to the Law, Technology and Design Thinking (LTDT) research group, to the recently established Law, Technology and Sustainability Transitions (LOST) research group. 

Applicants applying for this call must have a doctoral degree. Their expertise may cover several areas of law relevant to AI research, such as issues of legal theory or philosophy, fundamental rights, privacy, liability, contract or intellectual property law - to name a few. Moreover, experience of working in a multidisciplinary environment would be beneficial to the role.

The tenure track career path at the University of Lapland consists of three levels with different criteria. The position of Professor of Law and AI is open to all three tenure track levels. More detailed descriptions of the criteria for the levels can be found here: loader.aspx.  The Professor of Law and AI will be expected to:

• Conduct research in the field of law and AI and secure new external funding;
• Strengthen the Faculty’s presence in national and international networks in relation to AI related research, particularly existing ELLIS networks;
• Bridge multidisciplinary cooperation between ULap’s faculties and units to stimulate AI related research;
• Be ULap’s intermediary between academia and society on legal and ethical questions concerning AI;
• Strengthen the curricula by delivering course material on law and AI;
• Recruit and supervise M.Sc. and PhD students on topics related to law and AI.

Further information

Vice Dean of research Rosa Ballardini / Administrative manager Tiina Leppänen (email: firstname.lastname@ulapland.fi) 

The Faculty of Information Technology and Electrical Engineering and the Faculty of Medicine at the University of Oulu invites applications for tenure-track positions at the Assistant Professor level. If a suitable candidate is found, the position may be filled as a PS Fellow position. The professorship focuses on the theoretical and algorithmic principles of distributed or robust AI, with potential specializations in machine learning, including but not limited to wireless networks, multimodal signal and image analysis, ethical and explainable AI, computer vision, edge computing, cybersecurity, medical engineering, health AI, or robotics and autonomous systems. The faculty and its research team focusing on one of the listed specializations will be selected based on the candidate’s research focus and discussions during the on-site interview. 

 This assistant professorship position is sought to specifically strengthen research excellence while also contributing to teaching.  We welcome applicants from all backgrounds, including people of different ages, genders, and lingual, cultural, or minority groups. The position has a competitive salary as well as a competitive start-up package. The contract includes occupational health benefits. Relocation services are also available for people coming from abroad. 

Requirements and Process 

This call is for Assistant Professor positions only. Applicants must have a doctoral degree in computer science or related fields, with a strong publication record in machine learning, including top-tier conferences/journals. 

The selection process follows the University of Oulu´s recruitment guidelines. Short-listed candidates will undergo an expert evaluation. The eligible candidates fitting best in the profile expected for the position will be invited to an on-site interview. Tenure track members 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. Career progression is based on performance assessments considering these areas.

For detailed requirements and application instructions, please refer to the main call text.

Further Information

Please contact (emails: firstname.lastname@oulu.fi)

• HR Partner Ellinoora Blomqvist in recruitment process-related question
• Professor Mehdi Bennis, wireless networks
• Professor Janne Heikkilä, computer vision, multimodal signal and image analysis
• Professor Juha Röning, cybersecurity, mobile robotics
• Professor Steven LaValle, robotics and autonomous systems
• Professor Simo Saarakkala, medical engineering and health AI (multimodal signal and image analysis), general inquiries related to the Faculty of Medicine
• Dean Jukka Riekki, general inquiries related to the Faculty of Information Technology and Electrical engineering

More information

• Faculty of Information Technology and Electrical Engineering, https://www.oulu.fi/itee
• 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
• 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 Applied Artificial Intelligence. The successful candidate will build on one of the University’s recognized areas of excellence and extend it in new directions through novel algorithmic and/or data-oriented AI research. Potential areas of focus include, but are not limited to, autonomous systems, medical imaging, computational digital humanities, AI agency and safety, and national security and defense. 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—with its strong existing algorithmic AI research—and may be co-hosted by another faculty aligned with the candidate’s area of application.

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. Filip Ginter (Head of TurkuNLP) filip.ginter@utu.fi or Prof. Jaakko Järvi (Dean of Faculty of Technology) jaakko.jarvi@utu.fi with questions about the position, and Ms. Sanna Hirvola sanna.hirvola@utu.fi (Head of Administration, Faculty of Technology) with questions about the recruitment process.  

• Faculty of Technology

• Welcome to the University of Turku, relocation guide

The Faculty of Technology at the University of Turku invites applications for the PS Fellow Professor (full) or a tenure-track position at the Assistant / Associate Professor level in the field of Multimodal AI, combining the text and audiovisual modalities. The position is intended to strengthen and bridge our existing expertise in natural language processing (the TurkuNLP group) and computer vision/sensor fusion (Algorithmics and Computation Intelligence Group). Through the new position, we wish to expand our research in core areas such as:

• Cross-modal representation learning (e.g., joint embeddings of text and images, multimodal retrieval systems)
• Image–language grounding (e.g., visual question answering, image captioning, video–language navigation)
• Generative modeling (e.g., text-to-image synthesis, audio–visual scene generation, multimodal content creation), including multimodal LLM training
• Other relevant areas within the general area of Multimodal AI

The ideal candidate will be expected to lead impactful research programs in multimodal AI, collaborate with existing research groups to strengthen our overall profile in machine learning and AI, secure external funding, and build networks within the university, industry, and broader society. 

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 position is partially funded by a significant donation from Peter Sarlin, and one of thirteen PS Fellow professorships in Finnish universities; Sarlin’s Foundation PS aims to continue to support world-class AI research in Finland focusing on the PS Fellow network and ELLIS Institute Finland. The person appointed to the position is recommended to seek ELLIS Fellow or Scholar -recognition.

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. Filip Ginter (Head of TurkuNLP) filip.ginter@utu.fi or Prof. Jaakko Järvi (Dean of Faculty of Technology) jaakko.jarvi@utu.fi with questions about the position, and Ms. Sanna Hirvola sanna.hirvola@utu.fi (Head of Administration, Faculty of Technology) with questions about the recruitment process.

• Faculty of Technology

• Welcome to the University of Turku, relocation guide

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 University of Vaasa is seeking applications for a tenure-track Professor position in AI for Space Applications.  This position offers an exciting opportunity to drive research and innovation at the intersection of artificial intelligence (AI), machine learning (ML), space technologies, and the evolving space economy, with a particular emphasis on new space business models and their role in the energy transition. The position focuses on advancing AI-driven solutions for satellite-based solutions, autonomous systems, and intelligent data processing to support sustainable and commercially viable space technologies and applications.

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 data driven systems in space economy. Special consideration will be given to candidates whose work addresses:

• AI-driven solutions for the space economy, including satellite data analytics and advanced sensor data processing
• Integration of AI/ML with space technologies and data, addressing multidisciplinary sustainability topics
• Advancements in computing including edge intelligence, real-time decision-making, AI-enhanced remote sensing and positioning, energy efficiency

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. The tenure track level is determined by the applicant's merits and career stage.

Scope and task definition

The core philosophy underlying the multidisciplinary approach of the Cyber-Physical Systems (CPS) research team where this position is linked to 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 satellite data, smart systems, imaging, business and economic viability
• 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.

Further information

Mika Grundström, Vice President, University of Vaasa, tel. +358 29 449 8786, email: mika.grundstrom(a)uwasa.fi

Heidi Kuusniemi, Professor, School of Technology and Innovations, tel. +358 29 4498504, email: heidi.kuusniemi(a)uwasa.fi

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 Assistant 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 fund-ing and fostering industry collaboration.

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 

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. 

We are seeking applications for a tenure-track Assistant Professor position in Artificial Intelligence (AI) and Machine Learning (ML). If a suitable candidate is found, the position may be filled as a PS Fellow position. This position offers an exciting opportunity to contribute to research and innovation in the intersection of AI, ML, and Computer Science, with a particular emphasis on Energy efficient High Performance Computing (HPC).

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 with HPC. 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 computing solutions for AI
• Integration of AI/ML with technology focusing on autonomous systems, telecommunications, and smart environments.
• Advancements in HPC, including edge intelligence, real-time decision-making, balancing power

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. The tenure track level is determined by the applicant's merits and career stage.

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.

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 PS Fellow, Professor or Associate Professor in Machine Learning and AI Engineering within the tenure track career system. The selected person can, depending on their experience and competence, be appointed as Professor or as Associate Professor. An employment as Professor is continuous, whereas an employment as Associate Professor is fixed term, with the possibility of advancement to a full professorship and permanent employment. 

The position is part of the Information Technology unit at the Faculty of Science and Engineering, located in Turku and Vaasa. 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

The field of activity for the position is machine learning and AI engineering, with applications to any of the following areas: 

• data-driven green transition in industry
• high performance, energy efficient algorithms and low emission computing platforms for artificial intelligence and machine learning
• bioscience
• mission critical, secure and resilient software systems

We are looking for outstanding computer scientists with a strong research track record that can 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 research or industrial organizations. 

The position has a competitive salary, including  occupational health benefits, as well as a competitive start-up package. 

Requirements and Process 

An Associate Professor is required to hold a doctoral degree in computer science, computer engineering or a closely related field, possess solid experience in teaching, the capability  to lead research groups and raise funding for research, and strong experience in international research. Moreover,  proficient teaching capabilities are required. In addition, Professors are required to possess excellent 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.

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 present and discuss their research with our faculty. 

Further Information

Please contact the head of the unit Professor Ivan Porres or in recruitment process related questions HR Specialist Sabina Ringvall; 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
• Language requirements at Åbo Akademi: https://www.abo.fi/om-abo-akademi/jobba-hos-oss/information-om-sprakkunskapskrav-for-sokande-till-undervisningsbefattningar/
• Working at Åbo Akademi University https://www.abo.fi/en/about-abo-akademi-university/come-work-with-us/