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fields: Robotics Computer Science Electrical and Computer Engineering Mechanical Engineering Applied Mathematics Applied Physics Statistics and Optimization A strong background in robotics, machine
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collegial Department (29 faculty) that nucleates a larger interactive community (nearly 100 faculty). We support an exceptional Graduate Training Program, host two training grants, a robust weekly seminar
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biopsies and advanced, preclinical models. A combination of wet-lab and computational biology, close ties to the clinic, and a wonderful team of early career scientists give us the agility and expertise
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the PhD in Engineering programme. Make sure to reference the supervisor's name (Dr Farzad Hayati) in your application. Informal enquiries are welcome and should be directed to Dr Farzad Hayati at f.hayati
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and will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Ivan Rungger, National Physics
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Biomedical Engineering conducts leading research in image analysis, computer vision, and machine learning, with a growing emphasis on generative AI and AI for scientific discovery. Our mission is to develop
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stakeholders. Demonstrated ability to manage iterative feedback cycles and refine deliverables accordingly. The skills, qualifications and experience required to perform the role are: A PhD in Computer Science
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. About the organisation The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information
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Institute of Photonic Technologies to be undertaken within the College of Engineering and Physical Sciences at Aston University. Financial Support This studentship includes a bursary to cover the fees rate
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Funding: School of Computer Science Studentship consisting of the award of fees, together with a tax-free maintenance grant of £20,780 per year for 3.5 years. Lead Supervisor’s full name & email