211-0094/20-2K Professor of Data Science

Professor of Data Science
Department of Computer Science
Faculty of Science
University of Copenhagen


The Department of Computer Science, University of Copenhagen, is seeking to hire a full professor in Data Science. The professor will join a rapidly growing department, with strong research groups in Algorithms, Artificial Intelligence, Machine Learning, Natural Language Processing, Human Computer Interaction, Software Engineering, Data Management, and Image Analysis. We are located in Copenhagen, consistently recognized as one of the world’s most livable cities, in the country of Denmark, ranked as one of the top three happiest countries in the world.

Outstanding applicants in all areas of Data Science will be considered, but research areas of special interest include:

  • Interdisciplinary data science within the physical sciences
  • Interdisciplinary data science within the health and life sciences
  • Interdisciplinary data science within applied machine learning and artificial intelligence
We are looking for an outstanding, experienced researcher with an innovative mindset and intellectual curiosity to manage the Data Science Laboratory and strengthen and complement the research profile of the departments Machine Learning Section.

The Data Science Laboratory aims to enhance the quality of scientific data analyses in research carried out at the Faculty of Science, University of Copenhagen. This is done through courses, workshops, collaboration with researchers, and counseling of students and researchers. For further information, please visit https://datalab.science.ku.dk/english/.

The Machine Learning sections research is concerned with machine learning spanning from theoretical, over algorithm development, to solving concrete problems for science, industry, and society within: medical image analysis; bioinformatics and molecular biology; natural language processing and understanding; information retrieval and web data mining; multimodal processing; digital education and teaching technology. For further information, please visit https://di.ku.dk/english/research/machine-learning/.

The University of Copenhagen was founded in 1479 and is the oldest and largest university in Denmark. It is often ranked as the best university in Scandinavia and among the top Universities in Europe. The department of Computer Science offers a friendly and thriving international research and working environment with opportunities to build up internationally competitive research groups. The University of Copenhagen ensures working conditions that allow a healthy work-life balance and Copenhagen is a family-friendly capital city.

The department values interdisciplinary research and teaching and is actively involved in several cross-faculty research projects and educational programmes. Thus, the successful candidate must be capable of and interested in facilitating cross-disciplinary interactions both within the Computer Science Department and across the university. The candidate is expected to engage in interdisciplinary teaching, including courses for students with a non-technical background, e.g., health sciences.

Duties include the applicants own research, development of the field, assessment tasks, grant applications, and research management such as supervision and training of research fellows and other staff. The successful applicant must also teach, supervise, prepare and participate in examinations, and fulfill other tasks requested by the Department.

Selection Criteria

  • A world-class track record of high-quality research and scholarship as evidenced by publications in internationally leading journals and conferences.
  • A track record of leadership, including leading of a research group, effective management of academic staff, organization of workshops and conferences, and involvement in outreach activities.
  • A track record in attracting external research funding.
  • Drive, energy, and a vision for building and leading a world-class research group in Data Science.
  • Demonstrated capacity to teach effectively across a range of subjects, including the capacity to supervise undergraduate and graduate students; and develop curriculum and learning resources. Experience in interdisciplinary teaching will be an advantage. Applicants are required to have university level teaching experience, documented teaching competencies and must be able to explain and reflect upon own teaching practice and portfolio. Formal pedagogical training or supervision equivalent to the University of Copenhagen teacher training programme for assistant professors is required.
  • Good communication and interpersonal skills with the ability to establish and maintain effective working relationships with other researchers, students, and technical-administrative staff.
Assessment of applicants will primarily consider their level of documented, original scientific production at an international level, including contributions to developments in their field, and their documented teaching qualifications. Managerial and outreach qualifications of applicants including ability to attract external funding will also be considered.

Six overall criteria apply for professor appointments at the University of Copenhagen. The six criteria (research, teaching, societal impact, organisational contribution, external funding and leadership) are considered a framework for an overall assessment of the candidates. Furthermore, each candidate must be assessed according to the specific requirements stated in the job advertisement. Please read more at https://jobportal.ku.dk/videnskabelige-stillinger/kriterier-for-videnskabelige-stillinger/dokumenter-til-meritering/5c_Criteria_for_recognising_merit_-professors.pdf

Further information on the Department is linked at http://www.science.ku.dk/english/about-the-faculty/organisation/. Inquiries about the position can be made to Head of Section, Professor Christina Lioma, c.lioma@di.ku.dk, tel. +45 21 55 47 31.

Candidates may start from 1 September 2021 or as soon as possible thereafter.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff. Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.

Commencing salary is currently DKK 629.992 including annual supplement (+ pension DKK 107.728). Negotiation for salary supplement is possible. Note that Denmark protects the economic, social, and physical well-being of its workers, which includes robust health care, child care, elder care, and other generous benefits. Thus, direct salary comparisons across nations are typically not meaningful. Furthermore, unlike some north American universities, University of Copenhagen appointments are 12 months in duration and thus require no need for faculty to procure summer funding

The application including all attachments must be in English and submitted electronically by clicking APPLY NOW below.

Please include

  • Curriculum vitae including information about external funding
  • Diplomas (Master and PhD degree or equivalent)
  • Research plan – description of current and future research plans, including a short description of 5 particularly relevant papers.
  • Description and documentation of teaching experience and qualifications according to university guidelines
  • Complete publication list
  • Separate reprints of the above 5 selected papers
The deadline for applications is Monday 1 March 2021 23:59 GMT +1.

After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee.

You can read about the recruitment process at http://employment.ku.dk/faculty/recruitment-process/.

Interviews/trial lectures will be held on 7 June 2021.

Please refer to the following no. in future communication in this case: 211-0094/20-2K


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