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The Faculty of Arts is internationally leading for its research (https://www.arts.kuleuven.be/english/research ), home to a broad array of specializations and notable for the strong connection it
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both independently and as part of an international, interdisciplinary team Assets•Experience with computer vision or deep learning (e.g. PyTorch, TensorFlow)•Familiarity with street view imagery or other
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Informatics, Research Group Research-Development-Innovation is looking for a PhD-student with a doctoral grant. We invite applicants for a fully funded PhD position in machine learning, AI, and data science for
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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, proteomics, microscopy, structural biology, technology development, and bioinformatics at VIB-UAntwerp Center for Molecular Neurology (https://cmn.sites.vib.be/ ), at VIB (https://vib.be/ ), and at UBirmingham
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, or a closely related field Strong programming skills, e.g., Python, and familiarity with machine learning and/or software engineering workflows; experience with Git and empirical evaluation Experience
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publications and present them at well-known international conferences and workshops. Your profile M.Sc./M.Eng. Degree in telecommunication engineering, signal processing, machine learning or a closely related
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-Development-Innovation is looking for a PhD-student with a doctoral grant. We invite applicants for a fully funded PhD position in machine learning, AI, and data science for public health within the Electronics
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machine learning You have good programming skills in Matlab, Python You have proven your proficiency in English language equivalent to B2 level You are enthusiastic and result oriented You can work
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@kuleuven.be or Prof. dr. Frank Verbruggen, mail: frank.verbruggen@kuleuven.be.In case of problems with the online application, please contact solliciteren@kuleuven.be . Where to apply Website https