Summary
The Department of Computer Science (DIKU) at the University of Copenhagen offers two PhD fellowships in Neuro-symbolic Machine Learning specifically tailored for Biology and Drug Design. These fellowships aim to advance machine learning methodologies in combination with biological applications.
PhD Fellowships in Machine Learning for Biology and Drug Design, University of Copenhagen, Denmark
Designation
- PhD Fellowship: 2 positions available
Research Area
- Neuro-symbolic AI
- Biomolecular Machine Learning
- Drug Design and Pharmacology
Location
- University of Copenhagen, Denmark
- Potential research stay at the University of Edinburgh, Scotland
| Fellowship | Research Focus |
|---|---|
| PhD 1 | Tractable neuro-symbolic foundations for biomolecular machine learning |
| PhD 2 | Literature-aware neuro-symbolic modeling of GPCR interactions |
Eligibility/Qualification
- Background in machine learning, computational biology, computer science, bioinformatics, computational chemistry, physics, or mathematics.
- Experience in deep learning, probabilistic modeling, natural language processing, or structural biology is advantageous.
- No single background required; curiosity about biological or pharmacological questions is essential.
Job Description
- Conduct independent research projects under supervision.
- Complete PhD courses amounting to approximately 30 ECTS / ½ FTE.
- Participate in research environments including international collaboration.
- Engage in teaching and knowledge dissemination activities.
- Write scientific papers for high-impact journals and defend a PhD thesis.
How to Apply
Interested candidates must submit their applications electronically, including the following attachments:
- Motivated letter of application (max. one page)
- CV with educational background and relevant experience
- Original diplomas for Bachelor and Master programs, and transcripts
- List of publications (if applicable)
- Reference letters (if available)
Applications should be submitted through the university’s application portal.
Last Date to Apply
- May 21, 2026, 23:59 CET
For specific inquiries about the PhD fellowship, please contact Professor Wouter Boomsma (wb@di.ku.dk).
