Tenure Track position as Assistant Professor in Machine Learning

Umeå universitet, Teknisk-naturvetenskaplig fakultet 

The Faculty of Science and Technology at Umeå University welcomes applications for a tenure track position as Assistant Professor in Machine Learning. The position, which is established through the Wallenberg AI, Autonomous Systems and Software Program (WASP), comes with a substantial recruitment package (see below). Last day to apply is 2020-09-07.

Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. Software is the main enabler in these systems, and is an integrated research theme of the program.

The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry.” Read more at: https://wasp-sweden.org/

Work description  

  • Machine learning (ML) is the discipline of studying computer algorithms and software that can learn and improve autonomously through data. ML, including both neural network-based approaches and mathematical statistics-based approaches, has become a driving force behind many recent breakthroughs in artificial intelligence, and is used in widely different areas like speech recognition, image analysis, natural language understanding, machine translation, question and answering systems, protein folding, and even playing GO.

  • The primary focus for this position is research on advanced machine learning techniques, with focus on computational and method-oriented research and/or theory development. Your expertise should primarily be within the core areas of machine learning as e.g.:

  • ·       Data representation learning

  • ·       Explainability and interpretability of AI/ML systems

  • ·       Incremental learning and multi-task/transfer learning

  • ·       Interaction between AI, machines, humans and society

  • ·       Learning methods for estimating robustness, stability and reliability of AI/ML systems

  • ·       Learning with non-convexity (e.g., GANs, sequential learning, reinforcement learning)

  • ·       Statistical learning

Machine learning is a broad subject with connections to several departments at Umeå University. Four departments (Applied Physics and Electronics, Computing Science, Mathematics and Mathematical Statistics, and Physics) are participating in the call. The final departmental affiliation will be decided in connection to the employment.

The successful candidate will have an important role in developing the area of machine learning at the faculty. The candidate is also expected to develop collaboration across institutional boundaries inside and outside the university and within WASP, as well as to establish strong collaborations and obtain external funding from national and international funding agencies.

The purpose of the position is to make it possible to develop and establish long-term research activities. An assistant professor will be given the opportunity to develop his / her independence as a researcher, and is also expected to be engaged in research environments as well as in seminar activities, supervision of doctoral students and / or participate in postgraduate education courses.

The position is for 5 years, of which 80 % is for research and 20 % for pedagogical qualification/teaching. The position comes with financing for own salary and expenses for the full duration of the employment, plus salary and expenses for two postdocs (2 years each) and for two PhD students (4 years each). The holder of the position is expected to build a new research group and engage in WASP’s graduate school, WASP national meetings and other activities.

The position is part of Umeå University’s tenure track system, which means that an Assistant Professor has the right to apply for promotion to a position as Associate professor. Such an application shall be submitted at least six months before the end of the employment.


Those eligible for employment as an Assistant Professor (biträdande universitetslektor) are individuals who have been awarded a PhD, or equivalent academic competence. Preference should be given to those who were awarded a PhD or attained equivalent research competence no more than five years prior to the expiry of the application period for the position as assistant professor. A person who has been awarded a doctoral degree or has achieved equivalent expertise at an earlier date may, however, be considered in special circumstances. Special circumstances include sick leave, parental leave, and other similar circumstances.

We are looking for a candidate who has a doctoral degree in a subject of relevance for the position, or equivalent scientific competence.

A high level of proficiency in both spoken and written English is a requirement.

Assessment criteria and their weight   

In the selection of candidates, particular emphasis will be put on the degree of research expertise. In addition, the educational expertise and the ability to develop and manage operations and staff will be assessed. Furthermore, administrative expertise and other expertise of interest with respect to the subject matter and the duties to be included in the employment will be considered.

Research expertise  

Research expertise must relate to the core of machine learning, with focus on computational and method-oriented research, and/or theory development.

The degree of research expertise will be assessed on the basis of scientific work published in internationally well-respected scientific journals and conference proceedings that apply a peer review system and also on the applicant’s documented ability to develop and conduct research projects, where the quality, originality, and timeliness of the research contributions will be assessed.

Significant weight for assessment of the research expertise will be put on the assessment of the enclosed research plan where the scientific height of the proposed research, the relevance that the proposed area of research has for the objectives of the employment, and the degree of fresh thinking will be assessed. Postdoctoral experience from academy or industry is a merit. The successful candidate is expected to have significant international experience and having established active international research contacts. Documented experience of applying the research within different areas of application as well as documented ability to competitively obtain research funding is a merit.

Educational expertise   

Educational expertise should relate to the area of Machine Learning or related subjects. It will be assessed on the basis of documented experience and documented ability to plan and conduct research-based teaching and supervision at Bachelor’s and Master’s levels.

The criteria for assessment are:

  • ·       ability to plan, implement and evaluate teaching and an ability to supervise and examine students at every level of education

  • ·       ability to vary teaching methods and examination formats in relation to anticipated study results and the nature of the subject

  • ·       experience of collaboration with the surrounding society in planning and implementation of education

  • ·       participation in the development of learning environments, teaching aids and study resources

  • ·       a reflective approach to student learning and one’s own role as a teacher

  • ·       ability to convey relevant knowledge and skills, ,

  • ·       ability to stimulate students such that they drive their own learning process, to create engagement and interest in the subject area

Other assessment criteria 

The ability to develop and manage activities and staff refers to documented ability to initiate and lead research activities, collaborate with other research groups, and collaborate with the surrounding community.


The application should preferably be written in English and is to be submitted using the e-recruitment system of Umeå University, September 7, 2020 at the latest.

Please see instructions for what to include in the application, as well as how to describe the account of scientific and educational activities (link)


Further information can be obtained from faculty’s contact person for this position: Prof. Erik Elmroth, erik.elmroth@umu.se, +46-90 786 6986.

Consideration for promotion to Associate Professor  

An Assistant Professor shall, upon application, be promoted to Associate Professor if he or she is qualified for an appointment as an Associate Professor and upon review is deemed to meet the requirements for such appointment according to the assessment grounds to be applied in a promotion to Associate Professor. Such a promotion entails an open-ended contract as an Associate Professor. The application for review for promotion must be submitted six mo

nths before the fixed term appointment ends. If an Assistant Professor is not promoted after review, the fixed-term appointment ends. The criteria for promotion can be found in the employment profile established by the Dean of Faculty of Science and Technology June 9th, 2020.

Umeå University is dedicated to providing creative environments for learning and work. We offer a wide variety of courses and programmes, world leading research, and excellent innovation and collaboration opportunities. More than 4 100 employees and 34 000 students have already chosen Umeå University. We welcome your application!

Type of employmentTemporary position longer than 6 months
Contract typeFull time
First day of employmentUpon agreement
Number of positions1
Working hours100%
CountyVästerbottens län
Reference numberAN 2.2.1-794-20
Union representative
  • SACO, 090-786 53 65
  • SEKO, 090-786 52 96
  • ST, 090-786 54 31
Last application date07.Sep.2020 11:59 PM CET

Umeå University

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No deadline
Location: Sweden, Umeå
Categories: Assistant Professor, Computer Sciences, Machine Learning, Tenure Track,


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