Tenure-track assistant Professor in Data Science
Tenure-track assistant Professor in Data Science
Department of Computer Science
Faculty of Science
University of Copenhagen
The Department of Computer Science at the University of Copenhagen invites applications for a position as Tenure-track Assistant Professor in Data Science. The position is to be filled by 1 April 2023 or as soon as possible thereafter, subject to negotiation. The researcher will join a rapidly growing department, with strong research sections in the areas of Algorithms and Complexity, Machine Learning, Natural Language Processing, Human-Centered Computing, Software Engineering and Data Management, Programming Languages, and Image Analysis. The department is heading 2 centres within Artificial Intelligence: the SCIENCE AI Center (https://ai.ku.dk/) and the Pioneer Center within Artificial Intelligence (https://di.ku.dk/ai-centre).
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 consistently one of the top places in Europe. Within computer science, it is ranked number 2 in the European Union according to the Academic Ranking of World Universities (ARWU) 2021.
The Department of Computer Science offers a friendly and thriving international research and working environment with opportunities to build up internationally competitive research groups. There are good opportunities available to apply for research funding in order to establish oneself in Denmark. The Department of Computer Science has an experienced research support unit that offers mentoring and assistance when applying for funding. Further information on start packages and recruitment grants offered by Danish private and public foundations is available at https://www.science.ku.dk/english/research/recruitment-grants-and-start-packages/experienced-researchers/.
Copenhagen is one of the 10 most liveable cities in the world with a rich culture within music, theater and associations (https://www.visitcopenhagen.com). Life for families is made easy by a publicly supported daycare and health care system, dual career opportunities, maternity/parental leave and six weeks of annual vacation. International candidates may find information on living and working in Denmark at www.workindenmark.dk. Useful information is also available at The International Staff Mobility office (ISM) at the University of Copenhagen (https://ism.ku.dk). ISM offers a variety of services to international researchers coming to and working at the University of Copenhagen.
Description of the position
We are looking for a curious and open-minded Data Science researcher with an interest in interdisciplinary research collaborations. The researcher must have a strong foundation in Machine Learning (ML) in general and a key research area in an ML-centric topic. This key area could be within ML theory/methodology, but equally well be within areas that apply ML (see, for example, “Department profile and applicants below”). The successful applicant will have demonstrated research in their key research area at a high, international level. Ideally, this key research area can be linked with some of the Data Science Lab (DSL) application areas. Applicants with a track record in interdisciplinary data science research with applications in the natural sciences will be preferred.
The researcher will contribute to the research and teaching of the DSL at the Faculty of SCIENCE. The DSL supports interdisciplinary data science research at SCIENCE via collaborative projects and PhD courses. Thereby, a typical teaching activity could be a PhD course on applied machine learning with natural science applications following by project supervision of PhD students from these areas. Another teaching activity could be consultations with thesis students from the natural sciences, helping with data analysis and statistics in their thesis. The ideal applicant will see these teaching activities as an opportunity for creating interdisciplinary research collaborations, publications, and grant applications.
The DSL supports the departments at the Faculty of SCIENCE. This includes very diverse applicant areas for the data science collaborations (e.g., chemistry, biology, geography, human biology, physics, or other natural science areas), but also a broad spectrum of skills in programming, machine learning, and statistics. To support, educate, and learn from such a broad population, the DSL researchers need to also be generalists. Therefore, the applicant must not only be very strong in machine learning methods in general and deep learning methods in particular. The applicant must also be a strong programmer, be patient and eager to mature students/researchers at their own level, be strong in applied statistics, be superficially knowledgeable about physics/chemistry/biology, and be curious about all the fascinating areas of science that they will encounter. For further information, please visit https://datalab.science.ku.dk/english.
The successful applicant will be employed at the Department of Computer Science under the most appropriate research section (matching the researchers own key research area), see below. As a tenure-track assistant professor, the general duties include furthering the applicant’s own research, development of the scientific field, research assessment tasks, research 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. Finally, the successful candidate must be capable of and interested in facilitating cross-disciplinary interactions both within the Department of Computer Science and across the university, as well as internationally.
The tenure track assistant professor must have an academic standing showing internationally competitive research, and/or have internationally recognized high potential to make a future impact.
Department profile and applicants
The successful candidate will be attached to one of the department’s research sections (see https://di.ku.dk/english/research/). Particular fields where the research sections are looking to hire new faculty include, but are not limited to:
- Data management and governance for AI.
- Methodological research in Geometric Deep Learning.
- Methodological research in Robot Computer Vision
- Microscopy Image Analysis and Processing
- ML and sustainability, including environmental sustainability and applications of ML in the energy sector.
- ML theory and quantum ML.
- Natural Language Processing and Understanding of scientific documents.
- Process Mining and AI for Process Management,
- Scientific Text Mining and Knowledge Base Construction.
- Societal aspects of ML, including fairness and privacy.
We welcome any strong applicants that fit the “Description of the position above”, regardless of research specialization.
The position requires an increasing publication trajectory in high-level, international, peer-reviewed venues in the area of specialization, as well as some personal research grants or a designated (by name) part of grants. Research plans and publication record should delineate a clear potential for attracting external funding. An active network of international collaborations will be considered an asset. The tenure-track assistant professor must have an academic standing showing internationally competitive research, and/or have high potential to make a future scientific impact at the international level. Documented university level experience in delivering high-quality undergraduate/graduate teaching is not mandatory but will be an advantage. If not already holding formal pedagogical qualifications, candidates are required to obtain pedagogical training equivalent to the University of Copenhagen Teaching and Learning in Higher Education program for Assistant Professors.
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 Danish Ministry of Taxation and The Danish Confederation of Professional Associations on Academics in the State.
Note that Denmark protects the economic, social, and physical well-being of its workers, which includes robust health care, childcare, elder care, and other generous benefits. 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.
Negotiation for salary supplement is possible.
The tenure-track programme
Candidates hired as tenure-track assistant professors will be assigned a mentor who will provide the candidate with guidance related to career development, other academic topics and administrative procedures. Performance of the tenure-track assistant professor will be followed via internal yearly evaluations and a mid-term and final international evaluation by an assessment committee. If the ‘final appraisal’ is positive you will be promoted as associate professor. Performance and progression towards the criteria below will be evaluated with due consideration of differences between research fields.
Criteria for promotion
After a 6-year tenure-track period tenure-track assistant professors are expected to meet the following criteria:
- A strong publication track record within the specific field of research, including a significant number of corresponding authorships and at least some publications in high-ranked journals based on work carried out during the tenure-track period
- Strong external network of collaboration, including joint publications
- A significant track record of successful external research funding
- Establishment of a strong and internationally competitive research group demonstrating clear independence of former supervisors/mentors, or/and major contributions to the development of an existing research group demonstrating an ability to collaborate within the research group
- Completed https://www.ind.ku.dk/english/course_overview/up/ and established a teaching portfolio via participation in teaching, including preparation and development of departmental courses
- Successful supervision/co-supervision of MSc and PhD students
If the criteria are met, the tenure-track assistant professor will be promoted to Associate professor.
Assessment of applicants will primarily consider their level of documented, original scientific production at an international level including contributions to developments in their field, scientific profile in relation to ongoing research at the section, as well as documented teaching qualifications. Ability to attract external funding will also be considered as will managerial and out-reach qualifications. Teaching qualifications are not mandatory but documented teaching qualifications and teaching experience will be considered.
Six overall criteria apply for tenure-track assistant 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 the overall assessment of 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/5a_Criteria_for_recognising_merit_-Assistant_professors.pdf.
For more information about the Department of Computer Science, please visit our website https://di.ku.dk/english/
Inquiries about the position can be made to Head of Department, Professor Jakob Grue Simonsen (firstname.lastname@example.org) or Head of the Data Science Lab, Professor Erik Dam (email@example.com).
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Filing of application
The application including all attachments must be in English and submitted electronically by clicking APPLY NOW below.
- Curriculum vitae including:
- Please describe and document international network and relations
- Please describe and document internationally based activities
- Positions held at universities/research institutions outside Denmark
- Outreach activities, i.e. popular lectures or other activities in the media
- Grants held, personal or in part. Career development grants.
- Diplomas (Master and PhD degree or equivalent)
- Research plan - description of current and future research plans
- If available, description and documentation of teaching and supervision experience and qualifications- please describe and document:
- Experience with supervision of BSc and MSc students
- Teaching experience
- Formal pedagogical training
- Complete publication list
- Separate reprints of up to 5 particularly relevant papers
The deadline for applications is 23 October 2022, 23:59 GMT +2
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants to be assessed by an Assessment Committee. Note that being on the short-list, is not equivalent to being assessed qualified for the position. Short-listed candidate may potentially be deemed “not qualified” by the Assessment Committee. A sub-set of the qualified short-listed candidates will be selected for a formal interview by the Recruitment Committee.
You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.
Interviews/trial lectures will be held on 22 March 2023.
Please refer to the following no. in future communication in this case: 211-0141/22-2N.
Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and collaborative work culture – creates the ideal framework for a successful academic career.