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methods tailored to ILC. The PhD researcher will fine-tune and benchmark pathology foundation models using multi-site H&E and immunohistochemistry whole-slide images. The aim is to learn representations
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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
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organizes social activities, networking and upskilling events, and an annual PhD Symposium. Curious to know more? Learn all about what it means to start a PhD at VIB in our PhD Guidebook , written
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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, microscopy, spectroscopy, pore-structure characterization, geochemistry. You are interested in interdisciplinary research at the interface of materials science and microbiology and are motivated to acquire
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enrolled in ULB’s 4-year doctoral programme, in which they acquire many other important career skills. PROFILES Prof. Maes is looking for three highly motivated, intellectually curious, and collaborative
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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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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
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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