About the opportunity
The Computational Autoimmunity group at the Technical University of Denmark (DTU Health Tech) is seeking a highly motivated computational scientist with a strong foundation in bioinformatics and advanced machine learning. This PhD position offers an opportunity to push the boundaries of understanding Type 1 Diabetes (T1D) using ML-driven immune modelling in close clinical collaboration with Rigshospitalet in Copenhagen. The project combines large-scale public immune repertoire data with spatial transcriptomics data to bridge immune repertoire analysis and spatial context. The role is methodologically driven and embedded in a translational research setting with direct relevance to autoimmune disease biology.
Salary and benefits
- Fully funded 3-year PhD scholarship.
- Salary and appointment terms based on the collective agreement with the Danish Confederation of Professional Associations, with allowances agreed upon with the relevant union.
- An international, rewarding, and challenging work environment at a leading technical university.
Who can apply?
- A two-year Master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree in bioinformatics, computational biology, computer science, applied mathematics, or a closely related field.
- Strong passion for science and expanding human knowledge through research.
- Strong programming skills in R and/or Python.
- Experience with machine learning and statistics.
- Experience working with biological sequence and omics data.
- Excellent written and spoken English.
Required documents
- A letter motivating the application (cover letter)
- Curriculum vitae
- Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale
- Code repository (e.g., GitHub) or other documentation of programming projects, if available
When to apply
- Applications open upon posting.
- Deadline to apply is Monday, 31 August 2026 (23:59 Danish time).
- Applications are reviewed on a rolling basis, and interviews may be conducted before the deadline.
How to apply
- Open the online application link via 'Apply now'.
- Fill out the online application form.
- Attach all materials in English combined into one single PDF file.
Additional information
- Candidates may apply prior to obtaining their master's degree but cannot begin before having received it.
- As DTU works with research in critical technology subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates.
- Further information can be obtained from Associate Professor Leon Eyrich Jessen at ljess@dtu.dk.
Our Take on This Opportunity
This section reflects Open Opportunities’ own analysis of the opportunity from an applicant’s perspective.
You may be a strong fit if…
- Candidates with a Master's degree in bioinformatics, computer science, or applied mathematics.
- Researchers proficient in R or Python with a background in biological sequence and omics data.
- Individuals interested in translational research bridging immune repertoire analysis and spatial transcriptomics.
What should you think carefully about?
- The role requires on-site presence in Kgs. Lyngby, Denmark.
- Applicants must be prepared for potential open-source background checks due to critical technology research regulations.
- The position is highly competitive and involves a rolling review process, so early application is advised.
How could this fit your current goals and plans?
This scholarship is an excellent fit for a researcher aiming to build a career at the intersection of machine learning and immunology. It provides a structured three-year path to a PhD within a leading technical university, offering direct clinical collaboration that is ideal for those seeking to translate computational models into real-world medical applications for autoimmune diseases.
Our take
This is a strong opportunity for highly motivated computational scientists looking to specialize in T1D research; those without a strong foundation in both programming and biological data analysis may find the technical requirements challenging.
Ready to apply?
Review the opportunity on the official website before applying.
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