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candidate is expected to have a solid background in applied mathematics/statistics/computer science or related discipline. Advanced coding skills are a big plus. This position is fully-funded and research
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5.5 in all sub-skills. International applicants may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme How to apply
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, for example, embedding quantum sensors, clocks and encryption in a quantum communication network. The projects are suitable for students who have either an engineering or a physics background. The programme
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. Specific requirements of the project Minimum of an upper second class in Computer Science or related discipline. An MSc in Computer Science or related field will be an added advantage. A keen interest in
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technologies (phage-display) for stratification of fracture repair and bone regenerative treatments by gender. This project offers a unique interdisciplinary programme at the engineering, life science, and
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a strong background in Computer Science, Engineering, Maths or Physics, and preference would be given to those with a good understanding of computer vision and deep learning. It is essential to have a
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’. Use ‘Course Search’ to identify your programme of study: Search for the ‘Course Title’ using the programme code: 8090F. Research Area: Mechanical and Systems Engineering. Select ‘PhD Mechanical
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, Signal Processing, Machine Learning, or Computer Science. We welcome applicants onto the CDT from underrepresented groups. Closing date : 31th Aug 2024. Funding: Full-time studentships will cover UK
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OF THE PROJECT Essential Criteria: A first-class or upper second-class (2:1) degree (or equivalent) in a relevant discipline such as mathematics, computer science, AI, data science or statistics. Experience in
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-class or upper second-class (2:1) degree (or equivalent) in a relevant discipline (physics, mathematics, computer science, AI, data science or statistics). Strong candidates with sports science