449 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" positions in Belgium
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. Your core research tasks include: Developing advanced MBS/EHD models for drivetrain systems, incorporating transient tribological changes. Creating machine-learning-based surrogate models to enable rapid
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. These methods will integrate machine learning techniques and real-time sensor data, to enhance operational efficiency, reduce costs, and ensure desired service levels, such as meeting a high percentage of demand
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Deadline: April 15, 2026 Interviews: May 2026 Ideal start date: October 1, 2026 (some flexibility possible) Feel free to reach out informally to discuss the position. Website for additional job details https
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@kuleuven.be or Prof. dr. Johan Put, mail: johan.put@kuleuven.be . In case of problems with the online application, please contact solliciteren@kuleuven.be Where to apply Website https://www.kuleuven.be
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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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, May 4, 2026, at 8:00 CET. If you are invited for an interview, we may ask you to present the results of a take‑home assignment. Where to apply Website https://www.kuleuven.be/personeel/jobsite/jobs
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to collaborate with other research groups. The time to apply and improve your knowledge and skills on state-of-the-art in machine learning, (probabilistic) modelling, system identification and numerical
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-of-the-art office in Ghent, with the flexibility to work one or two days from home How to apply Please complete the online application procedure (https://jobs.vib.be/apply/131347 ) and include a detailed
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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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to ensure the learning of the essential basic concepts of fundamental immunology in the second year, as well as the knowledge and understanding of the host–pathogen relationship in the third year of