1,866 computational-physics-"https:"-"https:"-"https:"-"https:"-"Dr" Postdoctoral positions
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collaborative programme bringing together a team of leading experts in advanced electron microscopy imaging, first-principles modelling, metal halide semiconductor thin-film and device fabrication, and
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progression modeling. Explainability and interpretability of AI models to support clinical decision-making and regulatory compliance in healthcare settings. Scalability and computational efficiency in
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new £7m EPSRC funded Programme Grant that brings together a team of researchers from the universities of Durham, Leeds and Manchester investigating the formation of Molecular Solid Solutions (MoSS
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Trust-funded project on Plasma-Assisted Combustion (PAC) Modelling of Ammonia, in collaboration with the York Plasma Institute. The successful candidate will develop and apply advanced computational
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output in high-level peer-reviewed scientific journals. Your profile You must hold a PhD in Physics, Chemistry, Material Science, Computational Science, or similar. A high level of motivation to work in
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degree in Electrical Engineering, Telecommunications Engineering, Computer Science, Applied Physics, or a closely related field Strong background in communication systems, signal processing, and applied
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Professor; Dean of the Physical Science and Engineering Division; Chair of CREST), a Highly Cited Researcher in Materials Science and Fellow of MRS, APS, IEEE, NAI, IoP, RSC, and IMMM. About KAUST: KAUST is
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18.09.2024, Academic staff We have several 𝐏𝐡𝐃 & 𝐏𝐨𝐬𝐭𝐃𝐨𝐜 𝐨𝐩𝐞𝐧𝐢𝐧𝐠𝐬 in our Visual Computing & AI Lab in Munich! Topics have a strong focus on GenAI, including 3DGs, NeRFs, Diffusion
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efficient exploration of this multidimensional space. Working with the colleagues at the University of Liverpool, you will also help develop process¿optimisation algorithms toward autonomous operation and
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in experimental physics and superconducting device development, with a focus on advancing multipixel single-photon camera technology and multiplexed readout for quantum information science applications