48 machine-learning "https:" "https:" "https:" "https:" "https:" "Bournemouth University" PhD positions at University of Nottingham
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tailored trajectory guidance. Enhancing Robot Autonomy: Enabling robots to improve their own performance by learning from operator data, ultimately enhancing their ability to assist in complex tasks. Key
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extrapolated to increase the conservation of our built heritage at risk. Learning from previous earthquakes to increase resilience in future earthquakes in seismic areas (Feilden 1987) is essential to ensure
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transcripts. These should be submitted via email to Dr Taresco and through the University of Nottingham’s online application system (https://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx
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degree in engineering, maths or a relevant discipline, preferably at Masters level (in exceptional circumstances a 2:1 degree can be considered). To apply visit: http://www.nottingham.ac.uk/pgstudy/apply
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. These should be submitted via email to Dr Taresco and through the University of Nottingham’s online application system (https://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx ), selecting “Chemistry
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with a 1st class degree in engineering, maths or a relevant discipline, preferably at Masters level (in exceptional circumstances a 2:1 degree can be considered). To apply visit: http
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, preferably at Masters level (in exceptional circumstances a 2:1 degree can be considered). To apply visit: http://www.nottingham.ac.uk/pgstudy/apply/apply-online.aspx For any enquiries about the project please
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foundation in either machine learning or mathematical/computational neuroscience, demonstrable programming experience (Python/PyTorch), and the curiosity to work across disciplinary boundaries. A background in
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using multimodal approaches including advanced imaging, nano-mechanical characterisation and machine learning techniques Developing physics-informed reliability models using experimental datasets
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physics or computational data analysis (Python/R/MATLAB, machine learning, or bioinformatics) is highly desirable. Interested candidates should send a CV to michael.chappell@nottingham.ac.uk . Applications