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

63.600 € – 91.100 € pro Jahr

Befristeter Vertrag, Teilzeit

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63.600 € – 91.100 € pro Jahr

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Befristeter Vertrag

Teilzeit

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At the University Medical Center Hamburg-Eppendorf (UKE), we are committed to excellence in research, education, and comprehensive healthcare across our clinics. Every day, our team of approximately 17,000 dedicated employees works to make the world a healthier place. Our goal is to be one of the leading university hospitals while also being the best employer in our industry.

At UKE, we believe that meaningful and successful work should align with our employees personal needs and individual lifestyles. Just as diverse as these needs are, so too is the variety of personalized solutions we offer.

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

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Job-ID: J000006979

Contract Type: Temporary

Employment Type: Part time

Closing Date: 06.10.2026

Organization: UKE_Zentrum für Molekulare Neurobiologie (ZMNH)

Category: Research & Science

Department: Institut für Medizinische Systembioinformatik

Main tasks

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-or