Novo Nordisk Foundation Centre for University Science Education (NNF-USE).

The Department of Science Education invites applications for a three-year postdoctoral position in university statistics education research, commencing on January 1, 2027, or as soon as possible thereafter.

The position is part of the research project Toolbox Courses in Data Science at the NNF-USE, led by Professor Carl Winsløw. The postdoc will be part of the research group on Didactics of Mathematics, which hosts several other scholars working with stochastics education at all levels. Besides the researchers located at UCPH, NNF-USE involves partners from two other Danish universities (University of Aarhus, University of Southern Denmark) and from abroad.

Project Description
The teaching of statistics and more broadly data science to students of other sciences is not limited to introducing them to standard techniques including those furnished by computer software. To be efficient, students must learn how scientific questions are investigated by statistical methods based on further analysis of the context and questions, planning of data collection and careful analysis of the conditions under which statistical theory and techniques serve to analyse the data in view of addressing the original questions. In the project, pairs of service/toolbox courses on statistics/data science, and some corresponding undergraduate and graduate science contexts, will already have been analysed in the project, within the framework of the anthropological theory of the didactics (ATD), with curriculum analysis based on paths of questions, praxeologies and other methods. Both the project participants, and the courses and programmes in question, come from both the University of Copenhagen and the University of Aarhus; significant time will be spent at the second institution as well.

The Postdoctoral Position
Based on the curriculum analysis, the postdoctoral fellow will construct and experiment didactical designs for students in the courses, which could provide them with authentic experiences of data analysis in their broader field, such as nanoscience or machine learning. The fellow will have the opportunity to work and publish with experts of statistics and of statistics education, at the frontier of research on the interactions between modern science and methods in data science.

Expected tasks include in collaboration with project participants:

• Designing and experimenting study and research activities that relate questions in select sciences to statistical methods and theory;
• Collect and analyse data related to the experiments;
• Publish research results in high-quality international journals;
• Participating actively in the local research environment and project activities.

In addition, teaching and dissemination work will occupy approximately 20% of the work time, primarily within courses and projects hosted by the Department of Science Education. The successful candidate will receive training and certification in university pedagogy, to support both teaching here and in later career steps.

Who Are We Looking For?
We are looking for a highly motivated early-career researcher with a strong interest in statistics education and its roles in undergraduate and graduate science.

It is required that applicants:

• hold a PhD in statistics education or data science education by January 1, 2027, and a master degree in statistics or a closely related field;
• have documented teaching proficiency in university level statistics, preferably including courses for students of other natural sciences;
• are able to work independently as well as collaboratively in a research team.

It is considered an advantage if the applicant has experience with:

• research on statistics education in relation to one or more fields of natural science;
• design-based research in statistics education that involves collaborating with university teachers of both statistics and natural science in a research-intensive environment;
• research within the ATD.

Applicants should explain, for all six points above, how their publications and other documentation submitted demonstrate their qualifications in relation to each point.

Danish language proficiency is not required for the position. However, it is expected that applicants can communicate research clearly in spoken and written English and are willing to adapt to an environment where Danish is often used, for instance by attending a basic course in this language.

About the Department of Science Education
The Department of Science Education aims to open up science and mathematics for all through research that enhances education, communication, and public engagement. The Department brings together expertise from the sciences, social sciences, and humanities to lead internationally in science and mathematics education, digital education, history and philosophy of science, and science communication.

The Department currently employs approx. 100 persons – many of whom are international. We offer a vibrant interdisciplinary research environment and an attractive and friendly work environment for all employees, and we are determined to support PhD students, postdocs, and assistant professors in building of a foundation for their future career within and outside academia. It is a hallmark of our research to unite strong fundamental and applied research, with high impact in society.

A large part of the Department’s teaching activities concerns the mandatory university pedagogical training and competence development for teaching faculty at the Faculties of Science and Health.

You may read the Department’s strategy towards 2030 and you can read more about the department in general here: https://www.ind.ku.dk/english/

Terms of Employment
The average weekly working hours are 37 hours per week.

Salary, pension and other conditions of employment are set in accordance with the Agreement between the Ministry of Taxation and AC (Danish Confederation of Professional Associations) or other relevant organisation. Currently, the monthly salary starts at 39,993 DKK/approx. 5,350 EUR (August 2026 level). Depending on qualifications, a supplement may be negotiated. The employer will pay an additional 18.07 % to your pension fund.

Foreign and Danish applicants may be eligible for tax reductions, if they hold a PhD degree and have not lived in Denmark the last 10 years.

The position is covered by the Job Structure for Academic Staff at Universities 2025.

Application and Assessment Procedure
Applications must be submitted in English and uploaded electronically by clicking APPLY NOW.

The application must include:

• Cover letter describing qualifications and motivation for applying (max. 2 pages, including accounting for the seven points mentioned above);
• Research statement outlining relevant research experience and potential for contributing to the project on toolbox courses in data science (max. 2 pages);
• Curriculum vitae (max 1 page);
• Documentation of teaching qualifications (e.g. course certificates)
• Copies of Master’s and PhD diplomas (or documentation for expected PhD completion);
• Complete publication list;
• Up to three relevant publications (reprints or preprints);
• Names and email addresses of two references.

Application deadline: September 13, 2026, 23.59pm CET

After the deadline, applications will be assessed by an independent assessment committee. Shortlisted candidates will be invited for online interviews.

Further Information
For questions regarding the position or the project, please contact:

Professor Carl Winsløw
Department of Science Education
University of Copenhagen
Email: [email protected]

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

Københavns Universitet giver sine knap 10.000 medarbejdere muligheder for at udnytte deres talent fuldt ud i et ambitiøst, uformelt miljø. Vi sikrer traditionsrige og moderne rammer om uddannelser og fri forskning på højt internationalt niveau. Vi søger svar og løsninger på fælles problemer og gør ny viden tilgængelig og nyttig for andre.

Kontakt
Carl Winsløw
E-mail: [email protected]

Info
Ansøgningsfrist: 13-09-2026

Ansættelsesdato: 01-01-2027

Arbejdstid: Fuldtid

Afdeling/Sted: Department of Science Education