项目介绍

2026年7月14日

Department of Computer Science (DIKU) invites applicants for a postdoctoral position in Computer Science. The position is part of the project Differentiable Realism from AI and Modeling (DREAM), financed by the Novo Nordisk Foundation.

Start date is (expected to be) 1 January 2027 or as soon as possible thereafter. The position is for either 1 year or 2 years.

The project

This postdoctoral project will develop general self-supervised and unsupervised machine-learning methods for biological data where reliable labels are scarce, expensive, or impossible to obtain. The aim is to build methods that use unlabelled experimental data together with differentiable simulations to generate realistic synthetic datasets, transferable representations, and robust downstream models without relying on large human-labelled datasets.

There is freedom to influence the project, and the exact direction of the project will be defined in dialogue with the candidate. Possible methodological directions include generative distribution matching, domain adaptation, diffusion- or score-based models for noise and style transfer, contrastive and masked self-supervised learning, uncertainty-aware learning, and few-shot adaptation.

The project is rooted in scientific machine learning, with biological imaging and biophysical simulation as driving testbeds. We work with data that range from chromatin organization to microorganism tracking. A strong candidate may come from machine learning, computer vision, generative modelling, scientific computing, simulation-based inference, or a related area.

Who are we looking for?

We are looking for highly motivated candidates with a PhD or equivalent research experience in computer science, machine learning, scientific computing, physics, applied mathematics, engineering, computational biology, or a closely related field.

Relevant experience may include one or more of the following:

• generative AI, including diffusion models / flow matching, GANs, VAEs, normalizing flows, or energy-based models
• self-supervised, unsupervised, or semi-supervised learning and representation learning
• contrastive learning, masked modelling, domain adaptation, or unpaired translation
• synthetic-to-real learning, simulation-to-reality methods, or few-shot adaptation
• differentiable programming, automatic differentiation, and optimization in JAX, PyTorch, or similar frameworks
• scientific machine learning, inverse problems, differentiable simulation, or physics-based modelling
• computer vision, biological image analysis, microscopy data, or other noisy high-dimensional scientific data

The successful candidate should be able to conduct independent research, formulate general methodological questions, write and maintain research software, and collaborate with researchers working on application-specific projects and experimental validation data.

Our section

The project will be hosted by the IMAGE section, which performs research in machine learning, computer vision, and simulation. The section is a part of the Department of Computer Science, Faculty of SCIENCE, University of Copenhagen. We are located in Copenhagen.

Contact: Julius B. Kirkegaard. Email: juki@di.ku.dk

Foreign applicants may find this link useful: www.ism.ku.dk (International Staff Mobility).

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

The position is a fixed-term position limited to a period of 1 or 2 years. The starting date is 1 January 2027 or after agreement.

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 39,900 DKK/approx. 5,300 EUR (August 2026 level). Depending on qualifications, a supplement may be negotiated. The employer will pay an additional 17.1 % 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 2020.

Application and Assessment Procedure

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

Please include:

1.         Motivated letter of application (max. one page)

2.         Curriculum vitae including information about your education, research experience, software experience, language skills, and other skills relevant for the position.

3.         Diplomas for Master of Science and PhD degree, including transcript of records where available. If the PhD has not yet been completed, include a certified/signed statement from the institution or supervisor confirming expected completion.

5.         Include one publication, project, or code repository that you are proud of.

6.         Copy of your PhD thesis or thesis abstract (if available).

7.         Name and email address of reference(s).

8.         Publication list.

9.         Reference letters (if available).

Application deadline

The deadline for applications is 15 September 2026, 23:59, CET

We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.