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Field
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decision making, while you will be capable to apply machine learning and computational algorithms of social choice. This post is associated with following projects: Embedding EDI in the Distribution
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of how this machine functions. Elucidating the function is key to unlocking why certain mutations can cause disease such as early onset cardiac disease (through the muscle myosin protein) and how small
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: Erlangen Programme for AI” This is a 5-year programme supported by the EPSRC and is a collaboration of mathematicians and computer scientists at the University of Southampton, the University of Oxford (lead
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machine learning, data science, mathematics or a computational science), or a postgraduate qualification with a major statistical component. There is scope for the role to be undertaken in a hybrid manner
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Bezares (numerical relativity), Dr Stephen Green (gravitational waves, data analysis including machine learning, black holes), Dr Laura Sberna (gravitational waves, black holes, and environmental effects
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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proposals. Have a PhD in biostatistics or related subject with a numerate or computational component (including machine learning, data science, mathematics or a computational science), or a postgraduate
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postgraduate degree, ideally a PhD, in statistics, machine learning, or a related field. Experience of developing new statistical methods and a strong working knowledge of a statistical software package, such as
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a role model and fostering an inclusive working culture. Person Specification PhD, or close to completion, in a relevant, quantitative field, e.g. meteorology, machine learning, climate science
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or machine learning to complex data. The successful candidate will have (or be nearing completion of) a PhD in a relevant field such as polymer science, materials engineering, or mechanical engineering