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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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: If interested, please email Dr. Fayyaz Minhas (fayyaz.minhas@warwick.ac.uk) with the following: Your CV University transcripts A short statement explaining your interest in the project and how your background
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. Interested applicants should contact Dr. Tim Tang via email tim.tang@manchester.ac.uk with an updated CV. Suitable candidates will be asked to complete the electronic application form at The University
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://www.epsrc.ac.uk/skills/students/help/eligibility/ Enquiries: Informal enquiries may be made to Prof Richard Jones by email: r.k.jones@salford.ac.uk Curriculum vitae and supporting statement explaining
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science, engineering, mathematics, or related subject) Proficiency in English (both oral and written) Essential to have strong foundations in computer systems through degree courses or equivalent work experience
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developed. This project is available from 1st October 2025. Applications accepted until post is filled. Informal inquiries can be made via email to Prof. Chris Bennett (c.bennett@nottingham.ac.uk
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. Informal inquiries can be made via email to Prof. Chris Bennett (c.bennett@nottingham.ac.uk ). Eligibility: Due to funding restrictions this position is only available to UK candidates. Please apply here
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key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which
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. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please include details of your referees, including email address and
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Supervisors: Prof. Reinhard Maurer (Chemistry), Prof. Richard Beanland (Physics) Understanding how local atomic structure and long-range emergent magnetic and electronic properties in defective 2D