PhD Position (all genders) in Computational Biology and Deep Learning for Spatial Omics

We are a newly funded junior research consortium (BMFTR programme \'Zukunft eHealth\') of computational scientists, pathologists and nephrologists at UKE Hamburg and RWTH Aachen University Hospital, with a partner at Universitas Mercatorum, Rome. Our goal is to use spatial transcriptomics, digital histopathology and clinical data to understand the molecular basis of glomerular kidney diseases.

The position is jointly led by Dr. Robin Khatri and Dr. Lucia Testa. Robin Khatri develops computational methods for single-cell and spatial omics and their application to immune-mediated kidney disease, with recent work published in Genome Biology (2024), Nucleic Acids Research (2026) and Bioinformatics (2025), and, together with clinical collaborators, in Nature Immunology (2025), Nature Medicine (2024), Nature Communications (2024) and Cell Reports (2026). Lucia Testa works on geometric and topological deep learning, including neural networks on simplicial and cell complexes, with contributions in IEEE Transactions on Signal and Information Processing over Networks (2024), the International Joint Conference on Neural Networks (2023), the ICML Topological Deep Learning Challenge (PMLR, 2023) and Scientific Data (2026).

The consortium is embedded in the Institute of Medical Systems Bioinformatics (Director: Prof. Dr. Stefan Bonn) and the Hamburg Center for Translational Immunology, with access to clinical expertise in nephrology and to the bAIome high-performance computing infrastructure. The PhD student will be based in Hamburg, with regular joint meetings with the partner group in Aachen.

Your tasks

You will develop computational and machine learning methods to analyse and integrate spatial transcriptomics data of different resolutions and technologies, to characterise tissue organisation, and to derive data-driven molecular heterogeneity of kidney disease and relate it to clinical measures. Depending on your background and interests, the focus of your project will lie either on the integration and analysis of spatial omics data or on deep learning methods that exploit the higher-order structure of tissue, with the two projects closely linked. Methods will be released as open-source software, applied to a well characterised cohort of human kidney biopsies, and evaluated together with our partners. You will present your results at international conferences and publish in peer-reviewed journals.

This position is a fixed-term position for 36 months at 65% of the regular weekly work hours and is to be filled as of January 1, 2027 (or at the earliest possible date).

Our Offer

Fair and transparent compensation in accordance with our collective bargaining agreement ( TVöD/VKA ) (€ 63,600 – € 91,100), taking into account qualifications and professional experience. The salary range applies to a full-time position of 38.5 hours per week. The amounts listed are guidelines and do not constitute a salary guarantee.

Targeted and individualized professional development at both the technical and project levels is provided, offering long-term prospects in a meaningful work environment

Comprehensive continuing education and training programs at our UKE Academy for Education and Career

Opportunities to help shape our “UKE INside” personnel policy through cross-functional and cross-hierarchical projects

Sustainable commuting: Subsidies for the Deutschlandticket as a job ticket and Dr. Bike bicycle service

Excellent health, prevention, and sports progra