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the lifecycle of industrial systems. As machine learning sees broader adoption, companies are increasingly required to ensure the safety of machine-learning-enabled systems. The reliance on training data and the
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engineering Researcher Profile First Stage Researcher (R1) Country Belgium Application Deadline 31 Jan 2026 - 22:59 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU
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Software Testing and Analysis Machine Learning and Large Language Models Web Systems and IoT Systems The candidate must possess strong programming skills in Java or Python and is willing to learn all
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how a novel machine learning-based methodology leveraging reinforcement learning with human feedback and multi-objective optimisation can be realized to generate new and even improve existing work plans
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guaranteed. Given the real-time nature of these large complex infrastructures, machine learning techniques can complement more deterministic algorithms to guarantee a reliable operation of the system
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to that present in the LMC is recommended, e.g. on AI/Machine learning in drug design, assay development, bioconjugate chemistry, fragment-based discovery, DNA-Encoded Libraries (DEL), sustainability aspects, etc
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). Advantages strengthening the candidate’s profile, but strictly required: Experience with machine learning or system optimisation; proficiency in Python or MATLAB. Previous authorship or co-authorship
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interdisciplinary research project at IDLab-MEDIA (https://media.idlab.ugent.be/ ), UGent – imec, aimed at advancing the state of the art in motion capture, sensor fusion, immersive media, and 3D computer vision
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citation record must be focused on AI; or alternatively (B), machine learning engineers with an AI-focused PhD and demonstrated 2-year industry experience in AI development Applicants must have in-depth
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concepts such as digital twins, learning from human interactions. In the domain of efficiency and sustainability, projects relate to a.o. the development of novel electrical machines, engineering of