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(or international equivalent) in: Engineering, Mathematics, Computer Science, Physics, or a related discipline. We would also like to see enthusiasm for collaboration and software engineering, experience of C
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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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2:1 honours degree (or international equivalent) in mathematics, physics, engineering, computer science or other related discipline. To apply, please contact Dr Peter Brearley (peter.brearley
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or master’s course with substantial mathematical content, e.g. mathematics, statistics, physics, management science, or computer science. Early applications are encouraged, as candidates will be invited
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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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nature of this programme, we welcome applications if your background is in any biological, chemical or physical science or mathematics and are interested in using your skills in addressing biological
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and optimization of machine learning methods. Candidate’s profile An ideal candidate would typically have: a strong degree or higher qualification in a relevant field (e.g. computer science, mathematics
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necessary. Applicants will have a BSc degree/MSc in Computer Science, Mathematics, or a similar computational field. Funding This four-year studentship is funded by Cancer Research UK Cambridge Institute and
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, Synthetic Biology Applied Mathematics, Computer Science/AI, or Control Engineering Biological laboratory skills Programming / Software Engineering Electrical Engineering and robotics prototyping Application
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undergraduate honours degree in Engineering, Mathematics, Computer Science or Physics Excellent English written and spoken communication skills The following skills are desirable but not essential: Background in