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. This position is ideal for candidates interested in: operations research and optimization, climate adaptation and resilience, sustainable food systems, mathematical modelling and data-driven decision making
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, such that we can model systems consisting of a wide range of varying materials. These extensions will be employed and tested on actual measurement data as a benchmark. The project will involve mathematical
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, including efficiency, fairness, reliability, and sustainability. Despite recent advances, existing mathematical models often fail to jointly capture these aspects and trade-offs, limiting their ability
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Infrastructure? No Offer Description Challenge: Developing, operationalizing, quantifying, and embedding complex human and legal values into alignment pipelines for AI systems, open-weights, and foundation models
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hiring a doctoral candidate on the subject "Foundation AI models for distribution systems decision-making ". Foundation models have recently emerged as a new learning paradigm in AI. These models learn
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Job description The Delft University of Technology is hiring a doctoral candidate on the subject "Foundation AI models for distribution systems decision-making ". Foundation models have recently
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mathematical/statistical modelling and programming (e.g. Python, MATLAB, or similar). A research-oriented attitude and strong motivation to deliver ambitious, high-quality work. Ability to work in an
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of Advanced Computer Science (LIACS). As a team, we develop cutting-edge techniques for advanced computational imaging systems, combining expertise from Mathematics (Inverse Problems), Computer Science (Machine
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statistical learning theory and probabilistic models; prior exposure to notions of robustness, resilience, or uncertainty quantification is an advantage. Mathematical maturity and experience with formal
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focus We welcome candidates with a strong interest in developmental biology, organoid technology, and disease modelling. This position is part of the EU-funded Marie Curie doctoral network (VISI-ON-BRAIN