Are you passionate about science and developing and applying machine learning (ML) methodology to study the immune system and associated autoimmune disease states and mechanisms?

Then you may be the perfect candidate for this fully funded PhD Scholarship!

The Computational Autoimmunity group at the Technical University of Denmark, is looking for a highly motivated computational scientist with a strong foundation in bioinformatics and advanced ML. This PhD position offers the opportunity to push the boundaries of our understanding of Type 1 Diabetes (T1D) using ML driven immune modelling in a close clinical collaboration with the leading hospital in Copenhagen, Rigshospitalet. You will gain invaluable experience in augmenting and combining your technical skillset with concrete real-world application to patient data aiming to better the life of patients for the benefit of society.

Research focus, Responsibilities and Qualifications
Your focus will be on developing and applying machine learning methods to study immune mechanisms in Type 1 Diabetes. Specifically, you will investigate disease-relevant spatial organisation of immune cells in patient samples and develop computational approaches for identifying T-cell receptor (TCR) sequence and repertoire patterns associated with disease.

The project combines large-scale public immune repertoire data with spatial transcriptomics data generated in close collaboration with Rigshospitalet. A central ambition is to bridge immune repertoire analysis and spatial transcriptomics, linking TCR-level molecular patterns with spatially resolved tissue context. The project is therefore methodologically driven, while embedded in a translational research setting with direct relevance to autoimmune disease biology.

Your primary tasks will be to:

• Develop, benchmark, and apply ML methodology for pattern recognition in immune repertoire and spatial transcriptomics data
• Integrate heterogeneous public and project-specific datasets
• Interpreting computational results in close collaboration with clinical partners
• Communice findings through scientific publications and presentations at international conferences

Required qualifications
You must have:

• A two-year Master’s degree (120 ECTS) in bioinformatics, computational biology, computer science, applied mathematics, or a closely related field
• Strong passion for science and expanding human knowledge through research to make a difference
• 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

You must have 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.

Even if you do not meet every requirement, we encourage you to apply if you believe your skills and experience are a strong match for the role.

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.

Assessment
The assessment of the applicants will be made by an assessment committee chaired by Associate Professor Leon Eyrich Jessen, PhD, Section for Bioinformatics, Department of Health Technology, Technical University of Denmark.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union.

The period of employment is 3 years. Starting date is as soon as possible.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Associate Professor Leon Eyrich Jessen at [email protected].

You can read more about the Section for Bioinformatics here.

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.

Application procedure
Your complete online application must be submitted no later than Monday, 31 August 2026 (23:59 Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

• 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

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

Please note that applications will be reviewed on a rolling basis, and interviews may be conducted before the application deadline.

Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position.

DTU Health Tech
With a vision to improve health and quality of life through technology, DTU Health Tech engages in research, education, and innovation based on technical and natural science. We educate tomorrow’s health tech engineers and create the foundation for new and innovative services and technologies for the globally expanding healthcare sector with its demands for the most advanced technological solutions. DTU Health Tech’s expertise can be described through five overall research areas: Diagnostic Imaging, Digital Health, Personalised Therapy, Precision Diagnostics, and Sensory and Neural Technology. Our technologies and solutions are developed with the aim of benefiting people and creating value for society. The department has a scientific staff of about 210 persons, 140 PhD Students, and a technical/administrative support staff of about 100 persons of which a large majority contributes to our research infrastructure and related commercial activities.

The Section for Bioinformatics at DTU Health Tech develops computational methods and software for biological and biomedical research. Our research spans immunoinformatics, machine learning, systems biology, and translational data science, with strong collaborations across academia and clinical environments, both nationally and internationally.

DTU – For the benefit of society since 1829
DTU is one of Europe's leading elite technical universities. Through research and education at an international top level, we create solutions to the major societal challenges of our time and help secure Europe's global leadership in sustainable technological development. Since Hans Christian Ørsted founded DTU almost 200 years ago, our mission has remained the same: We develop and create value through the natural and technical sciences for the benefit of society. DTU has 13,800 students, 1,600 PhD students, and 6,500 employees. We work in an international environment and have an inclusive, stimulating, and informal work culture. DTU has campuses in all parts of Denmark and in Greenland and collaborates with the best universities around the world.

Location
Kgs. Lyngby, Denmark

Apply Before
2026-08-31T21:59:00+00:00