113 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Ghent University
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__Secure-ROLLOUT_TOKENPending Maximum Storage Duration: 180 daysType: HTTP Cookie __Secure-YECStores the user's video player preferences using embedded YouTube video Maximum Storage Duration
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students working on the early modern and modern Arabic corpus within the project You will be expected to design and teach academic courses on Arabic epigraphy and fieldwork methods, You will be responsible
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, United Nations University, ...).https://www.ugent.be/en/research/funding/globalsouthhttps://www.ugent.be/++resource++plone-logo.svg Ghent University actively participates in several development projects, financed
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of thermal energy and (hybrid) machine learning in which physics-based models are combined with data-driven techniques. Thermal cycles make it possible to meet the demand for heating, cooling, and electricity
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machine learning. This encompasses application domains such as industrial inspection, (ultra) high-definition video enhancement, smart multi-camera networks, computer vision, sensor fusion, and (medical
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to acquire them; demonstrate strong abstract reasoning skills; have a good command of English (working language). No prior knowledge of Dutch or French is required; willingness to acquire basic Dutch is
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perspective, including (but not limited to): machine learning and statistical learning computer vision and sensor-based data analysis natural language processing and large language models hybrid, interpretable
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with both experimental research and simulation software. You possess strong technical knowledge, expertise, and hands-on experience in the field of electric machines. Additional knowledge of power
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technical knowledge, expertise, and hands-on experience in the field of power electronics. Additional knowledge of electric motor design and the control of electric machines is considered an asset. You have
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researchers from IDLab-AIRO (robotic experts) and imec. Your main tasks include: Reviewing literature on decentralized control frameworks in the domain and machine learning algorithms compatible with