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Field
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of metal electrodeposition is largely lacking. Knowledge gaps remain on the exact mechanisms of conversion from solid oxides to metallic iron, as well as the exact physics and operation parameters
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We’re seeking for motivated candidates that are interested in developing computer models of the composite human neuro-muscular system that combine detailed musculoskeletal geometries, muscle-tendon
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positions: We offer two fully-funded 4-years PhD positions, with specific focus on Compositional Learning (PhD position 1) and Self-supervised Learning with priors (PhD position 2). The ReVision team will
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, such as quantum- and nanotechnology, photonics, biotechnology, synthetic biology and materials for energy storage and conversion, our faculty aims to provide solutions to important problems of the 21st
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collaborative. Proxy data will amongst others infer the stable isotope composition of foraminifera and mollusc shells, since not much is known about the changes in temperature and isotopic composition
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flow batteries (RFB), enabling affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e. complex material layers that can be optimized to specific battery
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method enables high-frequency strain, but the mechanism remains unknown. As a PhD, you’ll uncover how dynamic stress drives CO₂ conversion into valuable chemicals with minimal energy and waste. Ready to
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adaptation and learning from their experiences. Using a combination of theory, numerical experiments and precision desktop experiments, we will create 3D materials with self-adapting elastic elements
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candidate, and one Post doc. As a PhD candidate and postdoctoral researcher, you will conduct educational design research, i.e. a development study aimed at designing evidence-based solutions for complex
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postdoctoral researchers, supervised by Dr. Tim van Erven. This is what you will do AI and machine learning models keep getting better, but how they make their decisions often remains unclear, because