780 phd-studenship-in-computer-vision-and-machine-learning PhD positions in United Kingdom
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University of West London The Vice-Chancellor’s PhD Scholarships The University of West London is a forward-thinking University with an appetite for innovative, rigorous and impactful research. As
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Please quote reference: Quantum Computing at The School of Physical Sciences Duration: 3 years and 6 months. We are currently recruiting for the following full-time, fully funded PhD studentship
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members of staff. Research in the Department is organised into six themes : Causality; Computational Statistics and Machine Learning; Economics, Finance and Business; Environmental Statistics; Probability
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to date focus on just one layer, understanding what keeps AF going is challenging. This PhD project aims to bridge that gap by combining advanced machine learning tools with a new experimental protocol
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into car cabins (to reduce the exposure of occupants) and the regions where pollutants accumulate (to be avoided by pedestrians and cyclists) need to be minimised. The PhD objective is to study the effects
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/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition, applicants should be highly motivated, able to work independently, as
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: Dr James Yates, Director GSK Aligned programme of study: PhD in Mathematics Mode of study: Full-Time Project description: HIV remains one of the most persistent and challenging infections to cure due
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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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confidence level and required computational efficiency. Recent advances in Machine Learning (ML) offer promising means for developing hybrid ML-based ECTM models that can overcome computational deficiencies
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Location: UK Other Applications are invited to undertake a PhD programme, in partnership with Airbus, to address key challenges in ensuring adoption of sustainable approaches to fuel additives