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for photocatalytic degradation and H2 production.Designing multi-objective optimization algorithms to maximize environmental and economic performance. Your RoleAs a PhD researcher, you will: Build and validate hybrid
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at the KU Leuven, within the Biomed lab (https://biomed-kuleuven.web.app/research ) to develop new trustworthy AI algorithms for fracture detection based on novel photon counting CT technology. Particularly
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engineering or mathematical engineering Good understanding of statistics and machine/deep learning algorithms Interest in Biomedical data science Excellent programming skills in Python Proficient English, both
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optimization algorithms (e.g., SAT solving, constraint solving, MaxSAT, SAT modulo theories, Answer Set Programming, (Mixed) Integer Programming, ...). We offer a fully-funded postdoc position, initially for 12
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to express complex domain knowledge in a formal yet flexible manner, and (2) design AI approaches such as learning algorithms and reasoning engines that can exploit the provided knowledge? The successful
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-constrained platforms, without heavily relying on human interventions for hardware-aware optimization, or are unable to generate runtime-adaptive workloads, such as AI algorithms that evolve over time in
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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception