793 phd-studenship-in-computer-vision-and-machine-learning PhD positions in United Kingdom
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and establish their potential remain to be answered, both in terms of enabling technologies for distributed sensing and the techniques that exploit it. The focus of the PhD project is to improve our
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, building resilience and long-term sustainability. This fully funded PhD includes an enhanced stipend of £25,726 per year, undertaking an international placement, and completing a bespoke training programme
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the NIHR as part of EPR-HPRU between the University of Birmingham and UKHSA. In addition to the extensive training offered to all PhD students at UoB, the student will receive training and opportunities
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Funding Source: Warwick Industrial Fellowship (WIF) in partnership with Hydrograph Eligibility: UK only Supervisors: Professor Tony McNally, Dr Fengzai Tang Supporting Company: Hydrograph (see Home - HydroGraph ) Start date: 6th October 2025 Project Description – The aim is to develop a...
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The project aims to develop a publicly accessible in silico database that identifies and catalogues bacterial genes capable of altering the effectiveness of chemotherapy drugs in colorectal cancer (CRC) patients. Focusing on microbial modification of 5-fluorouracil (5FU), the study will...
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the solution of governing PDEs. - Train machine learning models to predict lifetime and failure based on loading and environmental histories. The PhD student will have access to world-class computing facilities
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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Research Office Location: Newport, Shropshire TF10 8NB Post Type: Full Time Contract Type: Fixed Term - 36 Months Closing Date: 23.59 hours GMT on Friday 21 November 2025 Reference: PHD-SELF-JAN
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Research Office Location: Newport, Shropshire TF10 8NB Post Type: Full Time Contract Type: Fixed Term - 36 Months Closing Date: 23.59 hours GMT on Sunday 01 March 2026 Reference: PHD-SELF-APRIL
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the effectiveness of an audio/visual online coaching programme that leverages digital health technologies as part of a novel intervention that can be easily accessed by a wide audience. This will be compared with