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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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development of (open source) tools and algorithms for numerical simulations; o supervise PhD students conducting research in the field of this vacancy; o take responsibility for project coordination
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medicine. This vacancy focuses on the algorithmic aspects of these techniques. We are seeking to recruit a strong researcher with a background in computer science. The ideal candidate can provide computer
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related field. The ideal candidate should have knowledge and/or experience in one or several of the following areas: Artificial Intelligence/Machine Learning algorithms and architectures Cybersecurity
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activities and support VOD services in their efforts to assess and reduce such footprint, in particular in their production and distribution activities. You will take an active participation in, and eventually
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-house database of experimental real-world data enabling large-scale validation of developed algorithms. Wind turbine drivetrains are critical components, and their failures can lead to significant
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science, mathematics, computational physics/chemistry or equivalent. The candidate: must demonstrate expertise in algorithmics/machine learning/artificial intelligence must show motivation in the interdisciplinary
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fluid-structure interaction (FSI); - Development of techniques for deforming fluid domains, including Chimera techniques. The doctoral research needs to realize algorithmic improvements in the topics
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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