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PhD in Causal Machine Learning for Real World Evidence Data at the University of Copenhagen University of Copenhagen in Denmark
Degree Level
PhD
Field of study
Computer Science
Funding
3-year PhD fellow employment with salary, pension, and terms in accordance with the Danish agreement for academics in the state. The position is employment-based rather than a scholarship and starts January 1, 2027, or after agreement.
Deadline
Sep 28, 2026
Country
Denmark
University
University of Copenhagen
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About this position
PhD opening in Causal Machine Learning for Real World Evidence data at the University of Copenhagen, within the Rasmussen Group at the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR). The project sits at the intersection of computer science, statistics, biology, medical science, and public health, with a strong focus on causal AI, machine learning, bioinformatics, and medical digital twins.
The PhD research aims to develop causal AI-based methods to better understand and predict cardiometabolic disease using large-scale health and biological data. The work will combine genomics, multi-omics, longitudinal health data, and modern machine learning to improve disease risk modeling, progression analysis, and treatment response prediction. The group describes itself as interdisciplinary, collaborative, and internationally oriented, with close links to clinical and international partners.
This is a 3-year PhD fellow position starting January 1, 2027, or after agreement. The post is based at CBMR, University of Copenhagen, and the employment terms include salary and pension according to Danish academic agreements. The position is conditional on successful enrolment as a PhD student at the Graduate School, Faculty of Health and Medical Sciences.
Eligibility highlights: Master’s degree in Biology, Bioinformatics, Data Science, or a related science; degree must be equivalent to a Danish two-year master’s degree. Applicants should also have a strong GPA, relevant qualifications, publications, work experience, and excellent English communication skills.
How to apply: Submit the application online in English via the Apply now portal. Required attachments include a motivation letter, CV, certified diploma and transcript, list of publications, and at least two references. Deadline: 28 September 2026, 23:59 CET.
Funding details
3-year PhD fellow employment with salary, pension, and terms in accordance with the Danish agreement for academics in the state. The position is employment-based rather than a scholarship and starts January 1, 2027, or after agreement.
What's required
Applicants must hold a Master’s degree in Biology, Bioinformatics, Data Science or a related science, equivalent to a Danish two-year master’s degree. Required qualifications include a strong grade point average, professional qualifications relevant to the PhD project, previous publications, relevant work experience, other professional activities, a curious mindset with strong interest in applying AI to health data, and excellent English communication skills (written and oral).
How to apply
Apply online in English via the Apply now link. Include a motivation letter, CV, certified Master’s diploma and transcript (with English translation if needed), list of publications, and at least two references. Submit before the deadline.
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