Tenure Track position as Assistant Professor in Machine Learning
Umeå University Department of Computing Science

Title Tenure Track position as Assistant Professor in Machine Learning
Employer Umeå University
Job location Biblioteksgränd 6, 901 87 Umeå
Published August 28, 2019
Application deadline October 14, 2019
Job types Assistant / Associate Professor, Tenure Track
Fields Statistics, Artificial Intelligence, Computer Communications (Networks), Software Engineering, Computational Mathematics, Machine Learning, Image Processing


Institutionen för datavetenskap

Temporary position longer than 6 months
100 %
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, http://wasp-sweden.org/), comes with a substantial recruitment package (see below). Last day to apply is 2019-10-14.


Subject description
Machine learning (ML) is the discipline concerned with computer software that can learn autonomously. 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. 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

The successful candidate will have an important role in developing the area of machine learning at the department. The candidate is also expected to develop collaboration across departmental boundaries inside and outside the University and within WASP.

The position is for 5 years, of which 80 % is for research and 20 % for pedagogical qualification/teaching. It includes a substantial recruitment package including full funding of two PhD candidates and two post docs.

The position is part of Umeå University's tenure track system. 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.


Eligible candidates must have a doctoral degree in Computer Science, Artificial Intelligence, Machine Learning, or a related area of relevance for the position, or has obtained equivalent scientific competence. In addition, relevant and documented scientific and pedagogical skills in the area of the employment is required. Applicants who have completed their degree no more than five years prior to the deadline for application will primarily be considered.

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

Assessment criteria
In the selection of candidates, particular emphasis will be put on the degree of scientific skills. Considerable weight will be put on the assessment of the enclosed research plan. In addition, the ability to develop and manage activities and staff as well as the level of pedagogical skills will be assessed. Furthermore, administrative and other skills of interest with respect to the subject matter and the tasks to be included in the employment will be considered.

Scientific expertise must relate to the core of Machine Learning, with focus on computational and method-oriented research. It's a merit if the research connects to some of the research topics at Umeå University mentioned above.

The degree of scientific skills will be assessed on the basis of scientific work published in internationally well-respected scientific journals and conferences 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. The scientific skills will also be assessed on the basis 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, as well as documented experience of applying the research within different areas of application. Documented ability to competitively obtain research funding is a merit.

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.

Pedagogical skills should relate to Machine Learning, or related subjects such as Computer Science or Artificial Intelligence. Pedagogical skills will be assessed on the basis of documented experience and documented ability to plan and conduct research-based teaching and supervision at the basic and advanced levels.

The application should preferably be written in English and is to be submitted using the e-recruitment system of Umeå University, October 14, 2019 at the latest.

Instructions for what to include in the application, as well as how to describe the account of scientific and educational activities can be found here:



Further information can be obtained from Head of Department, Erik Elmroth, elmroth@cs.umu.se.

Upon agreement

Erik Elmroth

+46 90 786 69 86

Registration number
AN 2.2.1-1186-19

Monthly salary

Union representative
SACO+46 90-786 53 65

SEKO+46 90-786 52 96

ST+46 90-786 54 31


before 2019-10-14

Umeå University wants to offer an equal environment where open dialogue between people with different backgrounds and perspectives lay the foundation for learning, creativity and development. We welcome people with different backgrounds and experiences to apply for the current employment.

If you apply for this position please say you saw it on Computeroxy


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