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scholarship is suitable for students with a background in Engineering, Mathematics, and Computer Science. Students with interests in machine learning, deep learning, AI, intelligent decision making
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related to early detection and chromosomal instability in cancer. A background in computational biology, mathematics, or computer science is preferable, though we welcome applicants with relevant biological
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. Funding This is a self-funded PhD, open to UK, EU and International applicants. Diversity and Inclusion at Cranfield We are committed to fostering equity, diversity, and inclusion in our CDT program, and
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the programme code: 8080F Research area: Statistics Select ‘PhD Mathematics (Full Time)' as the programme of study You will then need to provide the following information in the ‘Further Details’ section: A
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, Aerospace and Civil Engineering at the University of Sheffield, and embark on a transformative PhD project funded by John Crane Ltd, a global leader in engineering technology. What’s the Project About
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Two fully-funded 3-year PhD studentships are available in Neuromorphic and Bio-inspired computing at the interface between control engineering, electrical engineering, computational neuroscience
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need to contact the project supervisor to discuss. Online applications are made via the 'Apply' button above. Please select Engineering Mathematics* on the Programme Choice page. You will be prompted
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potential later start dates.) Supervisors: Professor Gwyneth Davies, Professor Rich Fry (Swansea University) and Professor Jenni Quint (Imperial College, London) Aligned programme of study: PhD in Population
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: Candidates should hold a UK (or international equivalent) first or upper-second Bachelor’s degree. Candidates with backgrounds in electrical and electronic engineering, physics, computer science and
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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had