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The PhD student position at Universitätsklinikum Hamburg Eppendorf is funded for 36 months at 65% of a full-time workload, based in Hamburg with regular meetings with the partner group in Aachen. It is part of a newly funded BMFTR junior consortium with clinical collaboration and access to GPU infrastructure.
You will develop computational and machine learning methods to analyse spatial transcriptomics data, integrate diverse data types, and derive data-driven insights related to kidney disease.
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.
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).
Please note that employment is contingent upon proof of immunization or immunity against the measles virus, in accordance with applicable legal and medical requirements. Documentation (e.g., vaccination certificate) must be provided before employment begins.
Dr. Robin Khatri
r.khatri@uke.de
+49 (0) 40 7410-52599
We offer a work environment that provides equal opportunities regardless of age, gender, sexual identity, disability, ethnic and social origin, or religion. This is confirmed by our accession to the Charter of Diversity. We explicitly aim to increase the proportion of women in management positions, especially among scientific personnel in research and teaching. Women with equal qualifications will be given priority. The same applies in the case of under-representation of one gender in the advertised area. Persons with severe disabilities with equal aptitude, competence, and professional performance will be given priority.