36 machine-learning-phd Fellowship positions at UNIVERSITY OF SOUTHAMPTON in United-States
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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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with physical objects/environments, and audio rather than video based AR can help enhance memory/learning Humanizing Computer Mediated Communication: Synthesizing co-presence - What does it mean to feel
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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modelling, satellite data assimilation, multivariate statistics, and machine learning. Prior experience with model and satellite products for mapping and understanding SM-dependent hazards (like floods
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funders. It is essential that you have a PhD in computer science, or equivalent professional qualifications and experience; ideally your PhD or equivalent professional qualifications and experience will be
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seek someone who can start immediately in October 2025. Applications for Research Fellow positions will be considered from candidates who are working towards or nearing completion of a relevant PhD
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electronics that can act as wearable doctors. This post is suitable for chemists or materials scientists with a PhD (awarded or imminent) in chemistry, materials science or a closely related discipline or
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laboratory. For informal enquiries about the project, please contact Prof Chris Holmes (christopher.holmes@soton.ac.uk ). To be successful you will have a PhD* (or equivalent professional qualifications and
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enquires about the project can be made to Dr Richard Meek (r.w.meek@soton.ac.uk ) About You You will have or be near completion of a PhD in biology, chemistry or related discipline, where you have gained
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successful you will have a PhD* (or equivalent professional qualifications and experience) in engineering, mechanical engineering, materials science or a closely related discipline. Experience in the synthesis