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algorithms capable of operating in large, partially observed spatial domains to infer efficient, interpretable strategies for estimating archaeological potential, that capture distinct criteria including
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strategies for estimating archaeological potential, that capture distinct criteria including scientific yield and cost effectiveness. These strategies will then be tested in real field settings (e.g. Turkey
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and adapt assimilation schemes based on generative deep learning methods (such as flow matching and diffusion models). The candidate should have previous experience in data assimilation and/or deep
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should be motivated to develop AI methods and apply them to clinically or epidemiologically meaningful research questions. We are particularly interested in candidates with experience in longitudinal data
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14 Jul 2026 Job Information Organisation/Company KU LEUVEN Research Field Computer science » Modelling tools Computer science » Programming Computer science » Systems design Technology » Computer
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, Trustworthy AI, Software Engineering, and Cybersecurity. The group is developing novel methods, tools, and platforms to support the safe deployment of AI systems in real-world environments. Current research
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working in a multidisciplinary photonic integration team led by Prof. Kasper Van Gasse within the Photonics Research Group of Ghent University and imec. The estimated breakdown of the research activity is
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University and imec. The estimated breakdown of the research activity is approximately 50% clean room work and process development, and 50% optical simulations (Lumerical, mode solvers, FDTD, inverse design