University of Copenhagen
1 month ago
PhD Fellowship in Simulation-Supervised Machine Learning for Biology University of Copenhagen in Denmark
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Sep 15, 2026
Country
Denmark
University
University of Copenhagen
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About this position
PhD fellowship in Simulation-Supervised Machine Learning for Biology at the Department of Computer Science (DIKU), University of Copenhagen.
This 3-year PhD project is part of the Novo Nordisk Foundation-funded DREAM project (“Differentiable Realism from AI and Modeling”). The research will develop simulation-supervised machine learning methods for biological data where reliable labels are scarce, expensive, or impossible to obtain. The central idea is to train models on synthetic data generated by biophysical simulations and to automatically tune those simulations so that the resulting synthetic datasets are realistic enough to generalize to real experimental data.
The project combines differentiable programming, biophysical simulation, differentiable rendering or signal generation, and machine-learning architectures aimed at reducing the simulation-to-reality gap. Possible directions include differentiable simulations in JAX or PyTorch, neural or physics-based rendering, generative distribution matching, and domain adaptation. One highlighted application area is chromatin organization, where simulations of DNA or chromatin structure could support machine-learning analysis of microscopy data, including segmentation, loop quantification, nucleosome spacing, or structural inference.
The position is hosted by the IMAGE section, which works on machine learning, computer vision, and simulation within the Faculty of SCIENCE at the University of Copenhagen. The call is aimed at highly motivated candidates with a strong background in computer science, machine learning, scientific computing, physics, applied mathematics, or a closely related field. Relevant experience in deep learning, generative modelling, computer vision, biological image analysis, scientific computing, synthetic data generation, and computational biology is especially relevant.
PhD supervisors: Julius B. Kirkegaard ([email protected]) and Jon Sporring ([email protected]).
Eligibility requires a completed degree equivalent to a Danish master’s degree related to the subject area. Applications must be submitted in English and include a motivation letter, diplomas and transcripts, CV, and other supporting documents where available. The application deadline is 2026-09-15 23:59 CET.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
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