The positions
The Department of Physics and Technology has up to three open permanent positions as Associate Professor and/or Professor. Early career scientists, with a promising CV, as well as experienced candidates are invited to apply, respectively for Associate and full Professor.
The faculty members will join the UiT Machine Learning Group. The group is internationally recognized, with research ranging from foundational machine learning methodology and algorithms to applied AI development. The range of applications is wide, with a particular focus on healthcare. The new faculty members shall further strengthen the scientific excellence and high-profile of the group, notably in the Centre of Research-based Innovation SFI Visual Intelligence, which is headed by the group, and the Centre of Excellence SFF Integreat – The Norwegian Centre for Knowledge-based Machine Learning.
The workplace is at UiT in Tromsø. You must be able to start in the position in Tromsø within 6 months after receiving the offer.
Your profile and field of work
You have a strong desire to develop the next generation machine learning methodologies. You find motivation by extracting knowledge from ever-increasing and challenging data, such as images, time series, tabular data, or other sources. You understand the importance of gaining insight, creating value, and solve real world applications of value to humankind and towards the UN sustainability goals. You find joy in teaching and you hold high ethical standards of your research, teaching and innovations.
Your interests are in neural networks research, where key research challenges are learning from limited data, interpretability and XAI, uncertainty quantification, and the integration of prior knowledge and context, or in general within self-supervised learning, unsupervised learning, representation learning, generative AI, graph-based learning, information theoretic learning, and/or neural knowledge-based learning. The Machine Learning Group has an internationally recognized expertise in developing theoretical and conceptual aspects of machine learning. This is strengthened by the recent centre of excellence SFF Integreat, where the group plays a major role.
Within the UiT Machine Learning Group and the SFI Visual Intelligence centre, the main applications are within health and medicine. Our research contributes to diagnosis and decision support by extracting patient-specific information from electronic health records and through medical computer vision for important clinical tasks such as cancer characterization. You can help transform healthcare for future needs, with AI as an integral part. Other relevant application areas include marine sciences for abundance estimation and sustainable harvest of the oceans, as well as environmental monitoring. Through machine learning, we can aid the climate, the oceans and Earth.
As a faculty member in the UiT Machine Learning Group, you will have the chance to make an impact on the world and to help shape the future of society with better machine learning solutions that are trustworthy and ethically sound. You are expected to collaborate with the current members in the group. The UiT Machine Learning Group relies strongly on teamwork and joint supervision of students. If you are applying for the Full Professor position, you are expected to bring your network of national and international collaborations and engage them in new connections with the group members.
Contact
Further information about the position and UiT is available by contacting:
Head of Machine Learning Group, Associate Professor Benjamin Ricaud; benjamin.ricaud@uit.no
Director of Visual Intelligence and Co-Director of Integreat, Professor Robert Jenssen: robert.jenssen@uit.no
Professor Michael Kampffmeyer: michael.c.kampffmeyer@uit.no
Associate Prof. Elisabeth Wetzer elisabeth.wetzer@uit.no
Associate Prof. Kristoffer Wickstrøm kristoffer.k.wickstrom@uit.no
Head of Department of Physics and Technology, Professor Olav Gaute Hellesø: olav.gaute.helleso@uit.no
Your qualifications and the evaluation
You must hold a PhD in machine learning or a related relevant field and you must document experience in executing independent original research.
You must have a strong background in machine learning methodology research with focus on developing novel methodology in deep learning (neural networks), probabilistic learning, geometric learning, knowledge-driven learning, information theoretic learning, or combinations thereof. Such qualifications must be documented by publications at a high level within machine learning journals and conferences such as IEEE TPAMI, IEEE NNLS, IJCAI, AAAI, ICML, NeurIPS, ICLR, CVPR, ECCV, ICCV, UAI, etc. Competence and experience with relevant applications, particularly in the health domain, will be emphasized, as well as interdisciplinary work. We are looking for a blend of research on generic methodology development and research towards specific applications.
You must be fluent in oral and written English and should have a good command of Norwegian or a Scandinavian language. Applicants who are not fluent in a Scandinavian language must be willing to learn Norwegian within 3 years and pass the language exam level B2 (“Bergenstesten” or equivalent).
UiT offers relevant Norwegian language courses for new employees.
We will evaluate contributions to cutting edge machine learning methodology, towards applications and inter-disciplinary work. At UiT we put emphasis on the quality, relevance and significance of the research work, in accordance with the principles of The San Francisco Declaration on Research Assessment (DORA). The publishing record will be assessed with respect to the career stage of the candidate, and we will emphasize the potential of the candidates more than the seniority. Teaching experience and your teaching philosophy and strategy will also be part of the evaluation. Documented external funding, experience with research leadership and relevant collaboration with industry for innovation activities will be rated positively for the Associate Professor position and will be an important aspect for the Full Professor position.
We will emphasize the applicant’s motivation for the position and personal suitability, including collaboration skills and approach to make a good work environment. UiT wishes to increase the proportion of female researchers in academic positions. In cases where two or more applicants are found to be approximately equally qualified, female applicants will be given priority.

QUALIFICATION REQUIREMENTS FOR THE POSITION AS ASSOCIATE PROFESSOR:

• Norwegian doctoral degree in subject area concerned or a corresponding foreign doctoral degree recognised as equivalent to a Norwegian doctoral degree, or competence at a corresponding level documented by academic work of the same scope and quality
• Documented pedagogical competence
  All applicants for teaching and research positions shall document their pedagogical competence. Those who do not satisfy the requirements may be appointed on a permanent basis on the condition that they satisfy the requirements within two years of appointment.

QUALIFICATION REQUIREMENTS FOR THE POSITION AS PROFESSOR:

• Academic level conforming to established international or national standards for position of Professor in the subject area concerned
• Documented pedagogical competence

In addition you must document:

• Development of the quality of one’s own teaching and supervision over time
• Broad supervision experience, preferably at master’s/PhD level
• Participation in the development of educational quality in academic communities

To be awarded a professorship, you must document substantially more extensive research of high quality than that required to be awarded a doctorate degree. You must document academic activity at a high level over the previous six years, and that this points forwards towards continued activity at professorial level.
UiT follows national guidelines for professorial promotion within Mathematics, Science and Technology disciplines when evaluating candidates for professorships.
Pedagogical basic competence
All applicants for teaching and research positions shall document their pedagogical competence.
You must have acquired basic competence for teaching and supervision at higher education level. This includes basic skills in planning, conducting, evaluating and developing teaching and guidance.

Please refer the Job description for details