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emphasis on technology transfer to industrial partners. Where to apply Website https://www.abg.asso.fr/fr/candidatOffres/show/id_offre/140019 Requirements Specific Requirements We are looking for two
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learning with mechanistic models; foundation models of genome regulation using single-cell and spatial multi-omics data; AI-based modeling of protein structure and protein interaction networks; AI-based
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above) grades. You have a strong background in deep learning. Previous experience with robotics, world models, reinforcement learning or other ML-based techniques for robot control is considered a plus
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counselling. In collaboration with the members of another teaching team, you will teach and coordinate the course Psychological Basic Skills for Conversation and Guidance (B-KUL-P0V87A). You hold a doctoral
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15 Jul 2026 Job Information Organisation/Company KU LEUVEN Research Field Educational sciences » Learning studies Educational sciences » Teaching methods Researcher Profile First Stage Researcher
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. The research will involve training machine-learning models on large structure and sequence datasets and integrating membrane-specific biophysical constraints to enable the design of membrane proteins and
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actively on the preparation and defence of a PhD thesis in the field of explainable reinforcement learning (XRL). Explainable reinforcement learning aims to make decisions, policies, and learning processes
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actively on the preparation and defence of a PhD thesis in the field of continual reinforcement learning. Continual reinforcement learning studies how agents can learn across a sequence of changing tasks
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sensing, advanced signal processing, machine learning, and longitudinal behavioral analysis to establish clinically meaningful digital biomarkers of eating behavior. These biomarkers will quantify fine
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of continual graph learning. Continual graph learning studies how graph neural networks can learn from a sequence of evolving tasks, graphs, or distributions while retaining previously acquired knowledges