Postdoc in Method development for AI-Generated T Cell Targeting Modules as at Technical University of Denmark

Kongens Lyngby, Capital Region of Denmark, Denmark -

Full Time

Start Date

Immediate

Expiry Date

02 Jun, 26

Salary

0.0

Posted On

04 Mar, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Deep Learning, Generative Models, PyTorch, JAX, HPC, GPU Clusters, Representation Learning, Protein Generation, Binder Design, Molecular Engineering, Protein Characterization, Cellular Validation, Computational Protein Design, Deep Learning Architectures, ML Frameworks

Industry

Education Administration Programs

Description

At DTU Bioengineering, we are developing next-generation immunotherapies powered by AI-driven protein design. We seek a highly motivated Postdoc to join the project “A novel AI-generated T cell targeting module – for precision immunotherapy” with start as soon as possible. The position centers on developing novel AI/ML methods as well as optimising existing ones to design recognition modules into functional immune cell therapies. The project is part of a large team that also allows close integration of AI-guided design and experimental validation. Responsibilities and qualifications In this project, we advance an AI-driven T cell-targeting strategy based on de novo-designed peptide-MHC (pMHC) binding proteins. Using computational protein design, we create synthetic recognition modules that enable engineered T cells to detect intracellular cancer antigens, expanding CAR-T and similar technologies beyond surface targets. You will help develop new and optimise existing computational design platforms for rapid deisgn and optimisation of novel targeting modules. Your responsibilities will include: Designing and implementing state-of-the-art deep learning architectures for protein generation * Developing and optimizing generative models for de novo binder design * Collaborating closely with wet lab scientists who will express and test the designs that have been created * Developing scalable training pipelines using modern ML frameworks * Generating data on miBd–pMHC interactions to guide iterative model optimization, espeicially for specificity * Benchmarking AI-designed recognition modules against existing targeting strategies * Contributing to the development of a scalable miBd library targeting clinically relevant cancer antigens * Publishing results in high-impact journals and contributing to future grant applications Experimental work will include molecular engineering, protein characterization, and cellular functional validation in engineered T cells. We are looking for a candidate who: * Holds a PhD in Computer Science, Machine Learning, Artificial Intelligence, Computational Biology, or a closely related field * Has strong theoretical and practical experience in deep learning * Has hands-on experience developing generative models * Is highly proficient in PyTorch and/or JAX * Has experience training large-scale neural networks on HPC or GPU clusters * Has experience with representation learning and sequence or structural modeling * Has a strong publication record in relevant AI/ML venues or interdisciplinary journals * Demonstrates the ability to work independently and drive technical innovation It will be considered an advantage if you have: * Experience with protein language models (e.g., ESM, ProtT5) * Experience with structure prediction frameworks * Experience in geometric deep learning or graph neural networks * Familiarity with computational drug discovery or molecular modeling * Experience with MLOps, reproducibility pipelines, or scalable AI systems As a formal qualification, you must hold a PhD degree (or equivalent). 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. Starting date is as soon as possible. The position is a full-time position. You can read more about career paths at DTU here [http://www.dtu.dk/english/about/job-and-career/working-at-dtu/career-paths]. Further information Further information may be obtained from Associate Professor Timothy P. Jenkins (tpaje@dtu.dk) You can read more about DTU Bioengineering at www.bioengineering.dtu.dk [http://www.bioengineering.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 [https://www.dtu.dk/english/about/job-and-career/moving-to-denmark]. Application procedure Your complete online application must be submitted no later than 18 March 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: * 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. The Department of Biotechnology and Biomedicine (DTU Bioengineering) is an international leader in the areas of biotechnology and biomedicine. Our engineering approach to all aspects of biotechnology and biomedicine positions us as a valuable player with unique competences in a growing bio-based economy and with health systems transforming towards personalized medicine. We have a clear focus on the needs in the life science- and biotech industries and point towards innovation, new businesses, and scientific services for the benefit of society. The department has extensive collaborations with national and international research units and industry. DTU Bioengineering has approx. 400 employees, of which 2/3 are scientific staff. The department is located at DTU Lyngby Campus. 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.

Responsibilities

The role centers on developing and optimizing novel AI/ML methods, specifically deep learning architectures and generative models, to design synthetic recognition modules (peptide-MHC binding proteins) for engineered T cell therapies. Responsibilities include developing scalable training pipelines, generating interaction data for model guidance, benchmarking designs, and publishing results.