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algorithms to shape the liveable cities of tomorrow? Job description Human-centred AI techniques, such as Reinforcement Learning from Human Feedback (RLHF), hold great potential for supporting design
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11 Apr 2026 Job Information Organisation/Company AMOLF Research Field Engineering » Design engineering Engineering » Microengineering Physics » Applied physics Physics » Optics Researcher Profile
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innovation with clinical relevance and real-world impact. Postdoctoral Researcher Explainable AI and Foundation Models for CT Imaging Our goal: To develop and validate novel AI methods that enhance
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track record in one or more of the following fields: (1) human-computer interaction, collaborative AI, (2) Generative AI/machine learning, (3) interaction design, experimental design, or evaluation
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(HIMS), in close collaboration with industrial partner BOR-LYTE and Smart Industry testbeds. This position offers a unique opportunity to combine inorganic chemistry, spectroscopy, machine learning, and
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team at AMOLF, working on fundamental questions on physical self-learning systems as part of the NWO ENW‑M1 project “How do physical learning systems learn?”. The research position is intended to start
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to develop generative AI methods for nanoparticle drug delivery design, at the intersection of machine learning, explainability, and pharmaceutical nanotechnology. Job description We are looking for a
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to play a role in designing and evaluating innovative and equitable educational approaches for multilingual learners? Come and join us as a postdoctoral researcher in a project aimed at developing
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Universiteit Amsterdam welcomes applications for a two-year Postdoctoral position in Reinforcement Learning for Stochastic Optimization. The candidate is expected to conduct high-quality research
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two crucial research questions: how do materials degrade in solution and solid phase, and what is the (extent of) correlation between these processes? While PhD candidates will design and apply new