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University of Copenhagen

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PhD Fellowship in Simulation-Supervised Machine Learning for Biology at University of Copenhagen University of Copenhagen in Denmark

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available

Deadline

Sep 15, 2026

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Country

Denmark

University

University of Copenhagen

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Keywords

Computer Science
Biomedical Engineering
Deep Learning
Biology
Computer Vision
Domain Adaptation
Bioimaging
Generative Modeling
Statistics
Physics
ML

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About this position

University of Copenhagen is advertising a PhD Fellowship in Simulation-Supervised Machine Learning for Biology in Denmark. The project is funded by the Novo Nordisk Foundation and focuses on developing simulation-supervised ML methods for biological data where reliable labels are scarce or impossible.

Research themes include machine learning, deep learning, generative modelling, computer vision / biological image analysis, numerical simulation and physics-based modelling, domain adaptation, synthetic data generation, and differentiable programming using JAX/PyTorch.

This is a PhD-level opening, not a postdoc or master's call. The post highlights salary information estimated at €53,000–€67,000 per year (median €54,000), indicating a funded doctoral fellowship.

Applicants should be prepared for research at the intersection of computer science and biology, especially if they have experience with ML methods, simulation, and image/data analysis. The post does not list detailed eligibility criteria such as degree class, GPA, or language-test requirements.

Deadline: 2026-09-15. How to apply: go to the University of Copenhagen employment portal and search for the exact title Simulation-Supervised Machine Learning for Biology.

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.

More information can be found here

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