Tenure track as Assistant Professor in Data Science - Befattningen är under tillsättning eller redan tillsatt, och det är inte längre möjligt att lämna in en ansökan

Umeå University welcomes applications for a tenure track position as Assistant Professor in Data Science with focus on data analysis and machine learning at the Department of Computing Science. The position, which is established through the Wallenberg Autonomous Systems Program (WASP), comes with a substantial recruitment package. Last date for application is October 31, 2016.

Work description
The emphasis of the position is data analysis and machine learning. The primary focus is on basic research that is expected to carry high industrial relevance in the long term. Examples of areas of expertise include learning for data streams, stochastic learning algorithms, big data analysis, data mining, deep learning, pattern recognition, kernel based learning, statistical learning, and reinforcement learning. Although expertise should be primarily in the core of data analysis and machine learning, the applicant should ideally also have experience from applying the research in some application areas. The appointment will be at the Department of Computing Science, and the recruited candidate is expected to collaborate with research groups in autonomous systems at Umeå University and in WASP.

The position offers stimulating and challenging tasks. A main criterion for employment is a strong commitment to research. The successful candidate will have an important role and large freedom in developing the area of data analysis and machine learning at the department, both in research and in undergraduate and graduate education. The successful candidate is also expected to develop collaboration across institutional boundaries inside and outside the university and within WASP.

The position includes a substantial recruitment package including full funding of two PhD candidates (four years each) and 2 post docs (2 years each). The PhD candidates will take part in the highly attractive national WASP Graduate School that started in early 2016 and already includes nearly 50 PhD candidates.

The position includes research as well as teaching and supervision at basic, graduate, and postgraduate level during 4 years until evaluation for tenure. During the 4 years, at least 80% of the time will be assigned to research and at most 20% to teaching, service, and related tasks.

The position is permanent and fulltime (100%). During the first four years the focus will be on the holders own research (at least 80%), however supervision, lecturing and improving your pedagogical qualifications will be included up to 20%. 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 tenure position as Senior lecturer / Associate professor. This must be done within four years.

Further information about employment conditions and benefits will be available from August 31 2016 at www.cs.umu.se/working_cs_umu.

Eligibility
Eligible candidates will have a doctoral degree in Computing Science / Computer Science, Artificial Intelligence, Data Science or equivalent scientific competence in an area of relevance for the position. In addition relevant and documented scientific and pedagogical skills in the area of the employment is required. Applicants who have completed their doctoral degree or equivalent degree no more than seven 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.

Scientific expertise must relate to the core of data analysis and machine learning, with focus on compute and method oriented research, rather than pure theory development. Documented experience from applying that expertise in an application area is an advantage, as well as documented ability to competitively obtain research funding.

Scientific skills will primarily be judged based on scientific papers published in internationally well-respected scientific journals, and in proceedings of scientific conferences that apply a peer review system, as well as documented scientific ability to independently organize, lead and manage projects. The quality, originality, and timeliness of the research contributions, as well as the research’s relevance to WASP, will be assessed. The scientific skills will also be assessed from the enclosed research proposal and the potential to develop an original line of research.

In addition, the level of teaching skills as well as administrative and other skills of interest with respect to the subject matter and the tasks to be included in the employment will be taken into account. Furthermore, the ability to develop and manage activities and staff at the university will be considered, as well as the ability to interact with the surrounding community.

Application
The application, preferably written in English, should include:

• A cover letter where you describe yourself, your main research area, summarize your previous research experience and describe your future plans
• Certified copies of relevant diplomas, grades and degree certificates
• A Curriculum Vitae containing academic and professional merits, including experiences from research and education
• A complete list of scientific publications including citation numbers
• Copies of at most ten relevant publications, numbered according to the list of publications
• A research plan describing the research you plan to pursue in this position (max 5 pages)
• Names and current contact information of three reference persons.

Umeå University is an equal opportunity employer, and welcomes applications from all suitably qualified persons. We strive towards an improved gender balance in science and technology.

The application is to be submitted on the MyNetwork Pro recruitment system October 31, 2016 at the latest.

Further information can be obtained from professor Erik Elmroth, elmroth@cs.umu.se, +46 90 786 6986.