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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
spatial multi-omics data; AI-based modeling of protein structure and protein interaction networks; AI-based modeling of cell morphology and tissue function using imaging and computer vision; AI models
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modeling of cell morphology and tissue function using imaging and computer vision; AI models of disease and digital twin applications. Biological applications and disease areas ideally focus on genetics and
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Network bringing together leading groups in structural biology, chemical biology, computational biology, drug discovery, and cell biology. Doctoral candidates will benefit from: International secondments
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join the Nelissen lab , and will work alongside scientists to develop and implement a mobile 3D machine vision system for small plants. The ideal candidate will have a background in mechanical
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computational design tools to engineer novel membrane proteins, then validate these designs experimentally, with the goal of integrating them into functional devices at the biology–electronics interface. Research
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research and to drive in vitro drug target and mechanistic discovery efforts using 3D triple culture system based on iPSCs. The cell lines will be derived from participants of the Flemish Cognitive Compass
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research and to drive in vitro drug target and mechanistic discovery efforts using 3D triple culture system based on iPSCs. The cell lines will be derived from participants of the Flemish Cognitive Compass
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computational approaches – including structural modelling, cheminformatics, and AI-driven methods – as part of the broader toolkit to enable program decisions, integrating computational predictions with rigorous
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morphology to directly link gene-regulatory cell states to functional neuronal phenotypes. This ambitious project integrates wet-lab experimentation with advanced computational analysis, and is ideal for a