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The MRC Brain Network Dynamic Unit (BNDU, University of Oxford) is seeking a Postdoctoral Research Assistant to undertake a program of research under the supervision of Dr Ashwini Oswal (Oswal Group
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The Robot Learning Lab in the Department of Computing at Imperial College London is seeking a talented Research Assistant (pre-doc) for an ambitious new project on dexterous robot learning. In
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topics would be advantageous: open system quantum optics, many-body physics, cold atom physics, computational physics, quantum physics, nano-photonics and metamaterials. The appointment will be for two
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying
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interdisciplinary research with leading academic groups across neuroscience, physics, and computer science, contributing directly to the future of neuromorphic systems. Key Responsibilities: Differentiate, grow and
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backgrounds to join our community. At the Department of Applied Physics, our pioneering research in physical sciences creates important industrial applications that hold great technological potential. Our
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Location: South Kensington Campus About the role: The Robot Learning Lab in the Department of Computing at Imperial College London is seeking a talented Research Assistant (pre-doc) for an ambitious
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We are looking for an outstanding early career researcher in Theoretical Astroparticle Physics to work with Samuel Witte in the Rudolf Peierls Centre for Theoretical Physics at the University
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, transitioning it from a promising research tool to a commercially attractive platform. Prof. Knowles' research group uses experimental and computational biophysics and physical chemistry to study human health and
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to completion) in atmospheric physics or related fields. Experience in atmospheric physics and track record in atmospheric modelling and the constraint of atmospheric models with observations are essential as