Postdoc in T Cell Immunoinformatics - DTU Health Tech

Postdoc position within T Cell Immunoinformatics with the aim of developing refined DL methods tailored to immune-receptors, able to integrate prior sequence to function domain knowledge, and involving strategies for data augmentation and data generation via active learning.
The Section of Bioinformatics, DTU Health Tech is world leading within Immunoinformatics and Machine-Learning. Currently, we are seeking a highly talented and motivated Postdoc candidate within the field of T Cell Immunoinformatics.

The immune system defends us against pathogens through immune cells specialized to mount precise and individualized responses. The dynamic behavior of the immune cell repertoire vitally determines health and disease outcomes. A key driver of this dynamism is the interaction between T cell receptors (TCR) and peptides from pathogen proteins presented by HLA molecules.

Large efforts have been dedicated to developing prediction models governing TCR interactions. However, overall the accuracy is limited, and characterizing and predicting these interactions remains a significant challenge. This, we postulate, is due to three interconnected challenges and conditions a) TCR diversity, b) limited quality and quantity of data biased towards a few well-studied epitopes and c) lack of Deep Learning (DL) tools tailored specifically to the particularities of TCR interactions.

As part of the Deep Immune Receptor Modeling (DIRM) grant from the NNF Data Science Collaborative Research Programme, this Postdoc position will seek to address this by developing refined DL methods specifically tailored to immune-receptors (IR) and able to integrate prior sequence to function domain knowledge, and applying iterative rounds of model refinement by use of active learning to rationally identify highly information-rich data to characterize experimentally.

This will result in DL tools and methods tailored and refined specifically to IR interactions and will for the first time bring DL into the field of immunoinformatics, furthering the development of predictive models with direct immunological and clinical translation and application.

If you are looking for the best possible foundation for establishing your scientific career and fulfilling your dreams and ambitions, this position could be your opportunity.

Responsibilities
The project will be conducted in an inspiring environment at the Section of Bioinformatics at DTU Health Tech as part of the IML research group led by Professor Morten Nielsen.

Your main focus will be centered on further developing the competences of the IML group within deep learning in the context of immunoinformatics in general and immune receptor in particular. You will work with nearby bioinformatics (in particular PhD students working both on the DIRM and other projects within the group) and experimental immunology colleagues.

Qualifications
As a formal qualification, you must hold a PhD degree (or equivalent).

The successful candidate must moreover exhibit the following professional and personal qualifications:

• Strong background within machine learning/deep learning, and immunoinformatics is a requirement
• Knowledge of the basic concepts of the cellular immune system is a plus
• Capability of taking personal responsibility for your work and your results
• Flexibility and a general positive attitude to changes
• Motivation by both individual and team accomplishments
• Strong communication skills in both written and verbal English

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 terms of employment
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 with starting date of 1 April 2025 or as soon as possible hereafter.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Morten Nielsen, [email protected] and at Immunoinformatics and Machine Learning (IML).

You can read more about DTU Health Tech at www.healthtech.dtu.dk.

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark.

Application procedure
Your complete online application must be submitted no later than 21 March 2025 (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:

• Application (cover letter)
• CV
• Academic Diplomas (MSc/PhD – in English)
• List of publications

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.

Section of Bioinformatics
The section of Bioinformatics within DTU Health Tech has its main research and teaching activities in bio-medical and bio-technological informatics, metagenomics, epidemiology, integrative systems biology and machine learning. The research at DTU Bioinformatics is focused on bioinformatics and computational analyses of large amounts of data generated within biological, biomedical and biotechnological and life sciences area. We strive to gain new knowledge and drive innovation in human, animal, plant and food science and collaborate with all relevant industries. A cornerstone in achieving this is the dedicated effort within DTU Bioinformatics to develop bioinformatics, immuno-informatics, metagenomics and systems biology methods and solutions to the challenge of handling and interpreting large scale and heterogeneous big data.

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.

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.

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