The Copenhagen Center for Social Data Science (SODAS) at the University of Copenhagen is an interdisciplinary research and teaching environment at the intersection of social science, statistics, and machine learning. SODAS conducts internationally leading research using large-scale administrative, digital trace, and textual data to address fundamental questions in the social sciences and to inform public policy.

The assistant professorship is affiliated with a newly funded research program developing transformer-based and foundation-model approaches for nation-scale administrative registry data, in close collaboration with Statistics Denmark and the Danish Data Science Lab. The project explores how sequential and representation-learning models can move beyond next-event prediction towards richer, policy-relevant signals, including heterogeneity in outcomes and treatment effects across populations.

The successful candidate will join a vibrant interdisciplinary environment with strong collaborations across the Faculty of Social Sciences, the Department of Computer Science, and external partners, and will have access to unique population-wide data infrastructures and high-performance computing resources.

The position is available from May 1, 2026, for up to four years.

Introduction
As part of the project you will be employed at SODAS. SODAS is an interdisciplinary research, teaching, and impact center situated at the Faculty of Social Sciences, University of Copenhagen. The center integrates traditional social science theories and methods with novel data science approaches, fostering a collaborative and international research environment. SODAS is home to over 40 researchers from diverse academic backgrounds and offers a supportive environment for both research and professional development. For more information, visit SODAS.

Duties and Responsibilities
Duties and responsibilities of the assistant professorship include contributing to the scholarship and intellectual life of the University by conducting world-class research and teaching. The assistant professor will contribute to the research, teaching, and academic development of SODAS. The primary responsibilities will be research-oriented and include:

• Conducting high-quality, internationally visible research on machine learning methods for large-scale sequential and administrative data, including efficient transformer-based and foundation-model approaches for specialized domains

• Developing and evaluating efficient and responsible modelling approaches for complex real-world data, including issues of robustness, bias, interpretability, and empirical validation in applied settings

• Contributing to collaborative research projects with Statistics Denmark and other academic partners, including co-authoring publications and participating in joint grant applications

• Participating in the supervision of PhD students and MSc projects within social data science, machine learning, and related fields

• Participating in the preparation of competitive external funding applications at national and international levels and contributing to the long-term sustainability and development of the research program.

Teaching duties will primarily involve contributing to existing courses within data science, machine learning, or computational social science, as well as the potential development of new course elements aligned with the candidate’s expertise. The expected teaching and supervision load is low (around 20%) and will be adjusted to support the candidate’s research profile and career development.

The assistant professor is also expected to contribute to the academic community at SODAS through participation in seminars, mentoring activities, and relevant administrative tasks.

Your Competencies and Opportunities
In order to be assessed qualified for an assistant professor position at the University of Copenhagen, the candidate must meet the University’s criteria of academic merit.

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 the overall assessment of candidates. Furthermore, each candidate must be assessed according to the specific requirements stated in the job advertisement.

You can read more about the criteria for recognizing merit for assistant professors here:

Criteria for recognising merit – University of Copenhagen (ku.dk)

5a_Criteria_for_recognising_merit_-Assistant_professors.pdf (ku.dk)

Applicants must hold a PhD (or equivalent) in computer science, data science, statistics, computational social science, or a related field by the time of appointment.

The successful candidate is expected to demonstrate:

• A strong research record in machine learning, natural language processing, or related areas, with publications in relevant international venues

• Experience adapting, evaluating, or developing transformer-based or foundation models for applied research problems

• Strong applied data science skills, including experience working with large, complex, or longitudinal datasets (e.g. administrative, health, social, or textual data)

• The ability to communicate technical results to interdisciplinary audiences and to collaborate productively across disciplinary boundaries

Experience with population-scale registry data or causal inference is an advantage but not a requirement. Candidates are expected to demonstrate the ability and motivation to extend their methodological expertise into new substantive domains, including policy-relevant applications in the social sciences.

The candidate should demonstrate teaching potential within machine learning, data science, or computational social science, as well as an interest in supervising MSc and PhD students in interdisciplinary settings.

The successful candidate will have strong interpersonal skills, a collaborative mindset, and the ability to work effectively in diverse research teams. A commitment to open, responsible, and reproducible research practices is expected.

Furthermore, the candidate must demonstrate a commitment to student learning, supporting student welfare and enhancing student experience.

Strategy of the Faculty of the Social Sciences
SODAS is part of the Faculty of the Social Sciences. The faculty is a successful academic community that strives to put knowledge into action by:

• Engaging partners in the co-creation of knowledge, learning and social change.
• Empowering our students to become reflective and responsible citizens who have the vision, the knowledge and the competence to change society for the better.
• Energizing global, European and Danish communities of knowledge by innovating research methodologies and by research findings with impact

For more on the Faculty strategy, see: https://samf.ku.dk/fakultetet/strategi/.

Terms of Employment

• Employment with the Faculty of Social Sciences and progression within employment will be determined only by personal merit. We do this by applying academic criteria of the University of Copenhagen which are related to the duties and conditions of each particular post and the needs of the Department concerned.
• As this is an assistant professor position, and therefore we strongly encourage the appointed assistant professor to acquire the proficiency in Danish required to teach and interact with colleagues in that language in 2-4 years. The Department will provide and pay for the necessary language training
• Further information on qualification requirements as assistant professor can be found in the Memorandum on Job Structure for Academic Staff at Danish Universities here: Bekendtgørelse om stillingsstruktur for videnskabeligt personale ved universiteter
• Terms of appointment and salary is in accordance with the Danish Confederation of Professional Associations (Akademikerne).
• The salary range starts at DKK 39,200 per month + a 18,07% contribution to the pension scheme. It is possible to negotiate salary supplements on an annual basis.

The recruitment process
Further information on the recruitment process at University of Copenhagen can be found here: https://employment.ku.dk/faculty/recruitment-process/

An Equal Opportunity Workplace
The University of Copenhagen is committed in its pursuit of academic excellence to equality of opportunity and to creating an inclusive working environment and therefore encourages all qualified candidates to apply, regardless of personal background, gender, sexual orientation, age, disability, ethnicity etc. For more on the diverse working place environment at the University and the University’s participation in the HRS4R HR Excellence in Research, see https://employment.ku.dk/working-at-ucph/eu-charter-for-researchers/

International applicant?
The University of Copenhagen offers a broad variety of services for international researchers and accompanying families, including support before and during your relocation and career counselling to expat partners. Please find more information about these services as well as information on entering and working in Denmark here: https://ism.ku.dk/

Contact information
Information about the recruitment process is available from HR, e-mail: hr-jur@adm.ku.dk. please refer to ID number: 211-0551/26-2A.

Additional information about the position can be obtained from the project lead, Associate Professor Andreas Bjerre-Nieslen, e-mail: abn@sodas.ku.dk, phone +45 35324417.

How to Apply
Submit a complete application at our online portal. Click on the “Apply now” icon at the bottom of the page to apply.

Your application must be written in English and include the following documents:

• Motivated application
  Curriculum vitae
• Certificates and Diplomas
• Publications. The 6 most important publications, of which at least three must have been published within the five years immediately preceding the deadline for application. The selected publications must be uploaded as attachments and named from 1 to 6.
• Publication list. A complete list of all publications with clearly marked publication dates. The uploaded publications must be marked with * on the list to be assessed.
• Teaching portfolio. Documentation of teaching qualifications in accordance with the University guidelines for teaching portfolios when appointing academic staff at the University of Copenhagen
• Documentation of ability to disseminate information. Documentation of the ability to disseminate information to and share knowledge with society.

Should any material submitted consist of work with named co-authors, or work that is otherwise the result of collective academic endeavors, the extent of the applicant’s contribution to the work must be clearly specified. The hiring committee may ask for a signed statement from the co-authors specifying the extent and nature of each individual’s contribution.

The closing date for applications is 23:59 [CET] 13 March 2026.

Applications or enclosures received thereafter will not be considered.