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Fixed-term: The funds for this post are available for 3.5 years in the first instance. Dive into the future of visual technology with a studentship at the forefront of modern imaging science, where
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practical solutions for safer participation. Projects may be supervised or co-supervised by experts from Engineering Science and the Medical Sciences Division. Potential Supervisors: Prof. Thomas Okell, Prof
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. What you should have: A 1st degree in physics or engineering. An interest in optics, some ability in computer programming A desire to learn new skills in complementary disciplines. You will work jointly
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(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
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strong upper second-class undergraduate degree in Chemistry, Physics, or a related discipline such as Mathematics or Computer Science, are encouraged to apply. The candidate is expected to have a strong
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, please select ‘Loughborough’ and select Programme ‘Mechanical and Manufacturing Engineering’. Please quote the advertised reference number * CSC-26-WS * in your application under the ‘Finance’ section
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settings, while providing essential process insights (such as electrode spacing, solvent chemistry, and operational voltage/current conditions) to support further technological development. Project specific
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will also work closely with our industrial partner on process engineering for a scalable prototype facility and product output testing. The successful PhD student will be supervised by Prof Anh Phan from
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: environmental monitoring, AI, computer vision or multispectral imaging. Entry Requirements At least UK equivalence Bachelors (Honours) 2:1. English Language requirement (Faculty of Science equivalent: IELTS 6.5
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in AI. Previous publication record in relevant fields: AI, machine learning, computer vision, etc. Previous successful project on a relevant topic. Good knowledge of statistics, probability