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-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process . An excellent technical
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, they will take an active role in designing and commissioning a pioneering Self‑Driving Lab, a next‑generation autonomous research platform that will integrate Machine Learning and Bayesian optimization
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–liquid interfaces through an integrated approach combining atomistic (DFT, AIMD, MD), and continuum (FEM) Modelling, supported by machine learning frameworks. Key responsibilities: • Perform DFT/AIMD
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within a Research Infrastructure? No Offer Description Modern robotics is at a pivotal point. While traditional learning-based methods have shown success in navigation and manipulation, they remain
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of their behavior. A particular focus of the thesis will be on the design and monitoring of collective systems populated by AI generative agents, and on improving their theory of mind, lifelong learning and social
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respectively, we seek highly motivated candidates to develop innovative methodologies for radar sounder data processing, with a strong emphasis on artificial intelligence and deep learning. The research activity
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techniques such as cross-domain alignment, robust representation learning, and embodiment-agnostic architectures. The goal is to create robot learning frameworks that can reliably transfer knowledge across
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take charge of your own learning process . An excellent technical infrastructure, on-campus children's day care and sports facilities. Unlimited access to the modern on‑campus TU/e Student Sports Center
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for more than 12 months in the 36 months immediately prior to your recruitment. Skills: Strong interest in AI/Machine Learning, Bayesian modeling and decision-making. Benefits Competitive Salary: Living
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the opportunity to grow into an independent researcher and/or future PhD candidate. Where to apply E-mail info@cobik.si Requirements Research FieldBiological sciences » BiologyEducation LevelMaster