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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine
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of Strathclyde will lead the wind energy training and research elements of the programme. Funded by EPSRC, this 4 year PhD studentship, at the University of Strathclyde is in the area of novel wind turbine concept
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: Starting October 2025, we require an enthusiastic graduate with a 1st class degree in engineering, maths or a relevant discipline, preferably at Masters level (in exceptional circumstances a 2:1 degree can
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Physics, Theoretical physics, Maths or other closely related subject (e.g. Materials Science with evidence of strong computational background and skills). To apply, please contact the supervisors; Dr Thomas
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Funding for: UK Home Student ONLY Funding amount: The studentship covers tuition fees and provides a tax-free stipend of £20,7802 pa for home student. The contribution of PV energy to
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PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience
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Supervisors: Dr Thomas Hudson, Maths, Dr Thomasina Ball, Maths Project Partner: Syngenta Many industrial companies dry their chemical products into powders to aid wide transportation and
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Supervisors: Dr Lukasz Figiel, Warwick Manufacturing Group, Dr Ferran Brosa Planella, Maths Project Partner: Jaguar Land Rover Efficient batteries for automotive industry are critical for achieving