PhD in Causal Machine Learning for Real World Evidence Data
Develop causal AI methods and medical digital twins using large-scale health and biological data at the University of Copenhagen.
Best for:Best for master's graduates in data science or bioinformatics with a strong interest in applying machine learning and causal inference to healthcare data.
Overview
The University of Copenhagen is inviting applications for a 3-year PhD fellow position within the Rasmussen Group at the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR). The successful candidate will focus on developing causal AI-based methods to model and predict cardiometabolic disease using large-scale health and biological datasets. The research aims to contribute to the creation of medical digital twins that capture individual health trajectories over time. Applicants will work in an interdisciplinary environment bridging machine learning, computational biology, and clinical research. The position is scheduled to commence on January 1, 2027, or by agreement.
What you'll do
- Design and implement novel causal machine learning algorithms to analyze large-scale health and multi-omics data.
- Develop computational medical digital twins to model disease risk, progression, and treatment response over time.
- Integrate diverse biological datasets including genomics, longitudinal health records, and clinical observations.
- Collaborate closely with international academic partners and clinical researchers on translational health projects.
- Prepare research findings for publication in peer-reviewed journals and presentation at international conferences.
- Fulfill the coursework, teaching, and dissertation requirements of the PhD graduate school program.
Requirements
Degree required: Master's degree in Biology, Bioinformatics, Data Science or related sciences equivalent to a two-year Danish master's degree.
Degree offered: PhD
Language: English; excellent written and oral communication skills.
Instruction: English
Publications: Previous publications are considered an advantage during evaluation.
- Strong background in machine learning, data science, or computational biology.
- Demonstrated interest in applying artificial intelligence to health and biomedical data.
- Proficiency in programming languages commonly used for data analysis and machine learning.
- Excellent written and oral communication skills in English.
- Must hold a relevant master's degree equivalent to a Danish two-year master's degree.
- Must be eligible for and successfully obtain admission to the Graduate School at the Faculty of Health and Medical Sciences, University of Copenhagen.
Funding & terms
How to apply
Deadline: 2026-09-28 (Europe/Copenhagen)
Candidates must submit their application online in English via the designated university portal. The submission must include a motivated letter of application, a comprehensive CV, certified diplomas and transcripts, a publication list, and contact information for at least two references.
- Motivated letter of application
- CV
- Master's diploma and transcript of records
- List of publications
- References
Contact
Simon Rasmussen· Professor
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