If you are a highly motivated computational scientist with a strong foundation in bioinformatics and advanced machine learning, this PhD position offers the opportunity to push the boundaries of immune repertoire modelling in a clinically relevant setting. 

You will design and develop novel machine learning frameworks for high-dimensional sequence data and apply them to large-scale public immune repertoire datasets and spatial transcriptomics data generated in collaboration with Rigshospitalet. This project will allow you to work at the forefront of methodological innovation in computational immunology while contributing to translational research in type 1 diabetes.

Research focus, Responsibilities and Qualifications
Your overall focus will be to develop and rigorously evaluate advanced machine learning models for high-dimensional T-cell receptor (TCR) sequence data and to investigate whether sequence-level disease signatures generalize across independent datasets and spatial transcriptomics contexts. The project combines large-scale public immune repertoire data with spatial transcriptomics data generated in collaboration with Rigshospitalet. You will work primarily on methodological development while contributing to a translational research setting in type 1 diabetes.

Your primary tasks will be to:

• Design and implement machine learning models for TCR sequence classification
• Develop reproducible pipelines for large-scale repertoire analysis
• Train and validate models on publicly available immune repertoire datasets
• Reconstruct TCR repertoires from spatial transcriptomics data
• Evaluate model transferability across datasets and biological contexts
• Perform benchmarking and comparative evaluation of machine learning models
• Disseminate results through publications and 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 programming skills in Python and/or R
• Documented experience with machine learning for high-dimensional data
• Solid understanding of statistics and model evaluation
• Experience working with biological sequence or omics data
• Excellent written and spoken English

Please mind that applicants with an 80% profile match are also encouraged to apply!

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.

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 june 1, 2026, or as soon as possible thereafter.

You can read more about career paths at DTU here .

Further information  
Further information may be obtained from Associate Professor Leon Eyrich Jessen at ljess@dtu.dk .

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 2 April 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.

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.

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. 

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. 

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, evolving, and informal work culture. DTU has campuses in all parts of Denmark and in Greenland and collaborates with the best universities around the world.