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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
(Group Leader at VIB and Professor (assistant professor, associate professor, professor or full professor) at KU Leuven, Dept of Computer Science and Dept. Electrical Engineering). We are particularly
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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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conditions, by bridging disciplines, from artificial intelligence, microelectronics, neuroengineering and nanoscience, to single-cell, imaging and molecular analysis, functional genomics and cell biology in
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gained to improve the sustainability of agriculture and the climate change resilience of crops. We are currently looking for an expert in Computer Vision, Image Analysis and AI to join our team. In
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, electrical or robotics engineering, and have expertise in building camera systems and computer vision. This role also involves working closely with the other members of the team on projects related to plant
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, electrical or robotics engineering, and have expertise in building camera systems and computer vision. This role also involves working closely with the other members of the team on projects related to plant
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, dynamics, and function of macromolecular complexes involved in health and disease. VIB combines excellence in fundamental research with exceptional opportunities for innovation and technology transfer
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the mechanisms of brain function and neurological disease across the scales of biology, spanning neurodegeneration, neurodevelopment, synaptic biology, and computational neuroscience. AI and large language models
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profile You have: a Master degree in engineering, computer science, mathematics or a related field a strong background in machine learning and AI (deep learning, LLMs, computer vision) strong proficiency in
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engineering, and computational biology, the bioinformatician will contribute to the implementation, automation, and scaling of NGS‑enabled analytics and AI‑driven nanobody–antigen structure prediction and