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KU Leuven, Department of Human Genetics, Leuven, Belgium, invites applications for a 48-month full-time PhD fellowship. The project focuses on zero-shot multimodal fusion models for rare disease prediction, integrating spatial and single-cell multi-omics with histopathology and clinical data.
Based in the MSCA SPACE-MEL network, you will develop machine-learning strategies for multimodal representation learning, access to high-performance computing, and secondments in international partner labs;
Host institution: KU Leuven, Department of Human Genetics, Leuven, Belgium
Supervisor: Prof. Alejandro Sifrim (KU Leuven, Belgium)
Co-supervisors: Dr. Martin Fergie, University of Manchester, United Kingdom (academic partner); Dr. Samantha Perona, Spotlight Pathology Ltd., United Kingdom (industry partner)
The PhD fellow will be based at KU Leuven, in the group of Prof. Alejandro Sifrim. The laboratory specialises in computational biology, artificial intelligence and statistical modelling for the integration of single-cell and spatial multi-omics data. KU Leuven offers a highly interdisciplinary environment, with expertise spanning computational biology, spatial omics and precision medicine.
The host laboratory provides access to advanced computational infrastructure, including GPU- and CPU-based high-performance compute servers and large-scale storage for multimodal data analysis. Through LISCO (Leuven Institute for Single-cell Omics), the candidate will also have access to state-of-the-art single-cell and spatial multi-omics technologies, imaging platforms and integrated bioinformatics resources.
The candidate will develop and benchmark zero-shot multimodal fusion models for rare disease prediction, using melanoma as a use case. The project integrates spatial and single-cell multi-omics data with histopathology and clinical information to learn robust cross-modal representations for diagnostic prediction. It pursues two integrated objectives: (i) to develop generative and explainable AI approaches for multimodal data fusion; and (ii) to extend existing multimodal frameworks with additional omics layers and evaluate their performance across heterogeneous datasets. At KU Leuven, the candidate will develop machine-learning strategies for multimodal representation learning and for the integration of the complex biological datasets generated within the consortium.
Duration and start date: 48 months, full-time. The first 36 months are funded by the MSCA Doctoral Network SPACE-MEL; the appointment is extended to a full four-year doctoral trajectory at KU Leuven. Intended start date: begin 2027.
Secondments: The project is carried out in close collaboration with the groups listed below, and visits to their laboratories are part of the training programme. These secondments take place within the contract period; a willingness to travel and to spend extended periods abroad is therefore essential.
The doctoral candidate will receive a competitive salary in accordance with the MSCA Doctoral Networks program, comprising a living allowance and a mobility allowance. A family allowance is foreseen where applicable.
KU Leuven additionally offers holiday pay, hospitalization insurance, reimbursement of certain commuting costs and access to its sports and childcare facilities.
A limited number of applicants will be invited for an interview and will be asked to provide the contact details of up to two referees.
You can apply for this job no later than October 15, 2026 via the online application tool
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