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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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extension to four years, will focus on leveraging the next generation of evolutionary algorithms to evolve efficient, robust, and interpretable predictors and data processing algorithms. A crucial aspect will
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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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algorithms (e.g., SAT solving, constraint solving, MaxSAT, SAT modulo theories, Answer Set Programming, (Mixed) Integer Programming, ...). Selection process For more information please contact Prof. dr. Bart
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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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in healthy states, genetically perturbed states, and during liver regeneration. On the other hand, you will develop algorithms to disentangle direct intercellular signals from those that are induced
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and algorithms for event-based fusion of two physically-colocalized event-based and depth vision sensors, simulate and analyse these models, and explore possibilities to realize them in CMOS ASICs
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theoretical background for MIMO related research, and have attended courses such as Information Theory, Signal and Systems, Modulation and Detection. Experience with OFDM or single carrier baseband algorithms
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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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