27 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" Fellowship positions at University of Birmingham
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-record in mentoring and supporting the development of early-career researchers. The profile and research interests of the group may be found at: https://www.birmingham.ac.uk/research/centres-institutes
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denotational semantics, abstract machines, as well as string diagrams and graph rewriting. Some knowledge of category theory would be useful but not essential. Being able to formalise the frameworks and
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friendly, supportive and collaborative working environment. The group brings together people with skillsets from across areas such as geotechnical engineering, archaeology, geophysics, sensing and machine
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experience in the use and/or development of machine learned interatomic potentials would be seen as a significant asset. Previous experience of inelastic neutron scattering spectroscopy (or similar) would be
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a uniform supersonic flow with minimal disruption to the flow characteristics • Lead in producing CAD designs of the optimized profiles in order for the profile to be manufactured (CNC machined
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to writing bids Operating within the area of gravitational-waves and astrophysics Applying probabilistic inference to gravitational waves, including through machine learning techniques Modelling
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of, computational models of decision-making (e.g. reinforcement learning, drift diffusion modeling, economic choice models) Experience of writing and publishing peer reviewed scientific papers on relevant topics (e.g
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research project. This project will be to acquire single-molecule localisation microscopy (SMLM) data of proteins in T cells. Role Summary Work within specified research grants and projects and contribute
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the Life Cycle Assessment (LCA) and TechnoEconomic Analysis (TEA), with regular workshops being held to remind ReLiB researchers of the need for these assessments and to teach them new sustainability
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new ones Willingness to learn and apply new scientific techniques Ability to access and organise resources successfully Proficiency in commonly used software packages and experience of data analysis