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group externally • Supporting laboratory capability, protocols, and scientific guidance within the team You should possess: • A PhD/DPhil (or near completion) in Engineering, Materials Science, Physics
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We are seeking a full-time Postdoctoral Research Assistant in Machine Learning to join Torr Vision Group at the Department of Engineering Science (central Oxford). The post is fixed-term for 1 year
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to an existing fleet-control system, while providing certified bounds on changes to closed-loop behaviour. The post holder will be a member of the Oxford Control Group and will develop new control architectures
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to specifically adjust targeted gene expression to reshape complex traits. The project will develop a breakthrough science-enabled technology platform to improve tomato heat, drought and nutrient deficiency
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fundamental research in physics-informed and symmetry-aware machine learning for nonadiabatic excited-state molecular dynamics. Develop and evaluate equivariant graph neural networks and related architectures
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engineering, science, shipping and architecture. With scientific excellence as a basis, Chalmers promotes knowledge and technical solutions for a sustainable world. Through global commitment and entrepreneurship, we
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Qualifications This position requires a PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Biomedical Imaging, Computational Biology, or a closely related field. Research Record: A strong
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this role, you will deeply understand the physics and operation of cryogenic scanning transmission electron (cryoSTEM) microscopes, and apply this understanding to design the architecture of entirely new
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students and fellow postdoctoral researchers within the laboratory and across EPFL’s international research network. Profile PhD degree in environmental engineering, microbiology, chemical engineering, or a
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
autonomy to work in close collaboration with a hardware engineer and clinical partners are all valued. A PhD in mechanical engineering, with expertise in shape/topology and system-level design optimization