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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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researchers and PhD students, pursuing research in many aspects of field theory, string theory, and integrability (for more information, see www.hw.ac.uk/uk/schools/mathematical-computer-sciences/research/maths
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will have or be close to the completion of a PhD in Neuroscience, Psychology or a closely related discipline. With in-depth knowledge of cognitive and computational neuroscience including motivation
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neuroscience or a related field. Experience of MEG/OPM-MEG acquisition and data analysis is essential. Experience with MATLAB or Python computer programming for neuroimaging data analysis is essential
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postdoctoral researcher with a background in politics, law, economics, or related disciplines to work on GEOCLOUD: The Geopolitics of Cloud Computing , a European Research Council Advanced Grant project
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Location: Department of Engineering Science, in collaboration with Experimental Psychology and in association with St Catherine’s College We are seeking a creative and highly motivated postdoctoral
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: Understanding of basic molecular biology techniques (PCR, qPCR) Understanding of basic cell culture techniques (media preparation, sterile conditions) Computer literacy is essential for the recording and
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You will have a PhD in Computer Science or a related discipline or will have obtained it by commencement of the position. Successful candidates will have experience of model training methodologies
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, coastal engineering including breakwaters and harbours, hydrodynamics, scour, vessels and offshore logistics The successful candidate will be engaged in planning, executing, analysing and reporting
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-generation AI hardware (ASIC) accelerators. The UK's Advanced Research Invention Agency (ARIA) is supporting an ambitious programme of work that aims to reduce the the cost of AI by more than 1000x: https