PhD Fellowship in Computational Pharmacology and Data Science at University of Copenhagen, Denmark

Summary

The University of Copenhagen is offering a three-year PhD fellowship in Computational Pharmacology and Data Science. This project, based at the Department of Drug Design and Pharmacology and connected to the Center for Pharmaceutical Data Science Education (CPDSE), focuses on investigating how genetic variants alter GPCR dynamics and drug responses using atomistic MD simulations and machine-learning approaches. The dopamine D2 receptor will serve as the primary model system.

Designation

PhD Fellow

Scholarship Details

Research Area

• Computational Pharmacology
• Pharmaceutical Data Science
• Structural Bioinformatics
• Statistical Genetics
• Cheminformatics
• Machine Learning for Drug Discovery
• Molecular Dynamics Simulations
• GPCRs (G protein-coupled receptors)

Location

Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.

Eligibility/Qualification

Academic Qualifications:

• For Danish Graduates: A relevant Master’s degree (equivalent to 180 ECTS BSc + 120 ECTS MSc).
• For International Graduates: A degree equivalent to a Danish Master’s degree (180 ECTS + 120 ECTS MSc), or a Bachelor’s degree equivalent to a Danish Bachelor’s degree (180 ECTS) with academic qualifications at Master’s level.
• Successful enrollment as a PhD student at the Graduate School at the Faculty of Health and Medical Sciences, University of Copenhagen.

Profile and Skills:

• Highly motivated and ambitious bioinformatician, data scientist, or machine learning specialist.
• Proficient with biologically driven questions, ideally experienced in MD simulations.
• Relevant experience with molecular modelling, molecular dynamics simulations, and/or analysis of molecular simulation data.
• Excellent programming skills, preferably in Python including code versioning in GitHub.
• Experience with statistical analysis and/or machine-learning methods.
• Knowledge of protein structure, structural bioinformatics, or molecular interactions; experience with GPCRs or membrane proteins is an advantage.
• A curious mindset with a strong interest in computational pharmacology, GPCRs, and pharmaceutical data science.
• Knowledge of cell biology, protein structures, and evolution.
• Strong written and spoken English and good communication and collaboration skills.
• Willingness to relocate to Copenhagen.

Scholarship Description

The PhD project aims to investigate how genetic variants influence GPCR dynamics and drug responses. The successful candidate will utilize atomistic Molecular Dynamics (MD) simulations to identify biophysical descriptors of receptor function and integrate these findings with machine-learning approaches to predict ligand- and variant-specific pharmacological outcomes. The dopamine D2 receptor will be the primary model system for this research.

Key Tasks as a PhD Student:

• Carrying out an independent research project under supervision.
• Completing PhD courses or equivalent education (approximately 30 ECTS points).
• Participating in active research environments, including a stay at another research team (preferably abroad).
• Obtaining experience with teaching or other dissemination related to the PhD project.
• Teaching undergraduate students in pharmaceutical sciences.
• Writing a PhD thesis.

The position offers creative and stimulating working conditions within a dynamic and international research environment, with access to a competitive computational core facility and modern research facilities.

How to Apply

Applications must be submitted electronically via the University of Copenhagen’s online application portal by clicking the “Apply now” button on the original job advertisement. The application must be in English and include the following documents in PDF format:

1. Motivated letter of application (maximum one page).
2. CV including education, experience, language skills, and other relevant skills.
3. Certified copy of original Master of Science diploma and transcript of records in the original language, including an authorized English translation if applicable. If not completed, a certified/signed copy of a recent transcript of records or a written statement from the institution or supervisor is accepted.
4. Publication list (if available).
5. References and recommendations (if possible).

Applicants with a Master’s degree from abroad should also enclose a short description of the grading scale used.

Last Date for Apply

26 September 2026, 23:59 (CEST)

Apply Link

Apply Now