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, including but not limited to computer science, data science, engineering or mathematics, who are passionate about machine learning and AI research. Strong analytical thinking, problem-solving skills, and the
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enhancing security measures within smart homes, including real-time monitoring and threat detection, while ensuring the privacy of residents. Applicants should have a good mathematical background, excellent
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capabilities to match the real outcome as closely as possible. Entry Requirements Acceptable first degree - Computer Science, Engineering, Physics or Mathematics. The standard minimum entry requirement is 2:1
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, Physical Sciences, Chemistry, Natural Science, Mathematics. Mode of study Full-time Start date 1 October 2026 Funding This PhD project is in a competition for a Faculty of Science funded studentship. Funding
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involve collaboration with our industrial partners. Projects provide a unique research and training experience and an exciting opportunity for you to develop mathematical innovation inspired by contemporary
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wellbeing and enabling inclusive decision-making for a greener, fairer and healthier future. The PhD will be based in the Environmental Mathematics group within the Department of Earth and Environmental
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entry requirements: The student should have a background in geoscience, civil, chemical or mining engineering. They should have strong mathematical background - it would be advantageous if the have some
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flows, and to have developed skills in experimental fluid mechanics, statistics, data processing, machine learning, and mathematical modelling. Supervisors: Dr Kostas Steiros Duration: 3.5 years. Funding
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undergraduate degree (or the international equivalents) in engineering, computer science or mathematics and statistics, we would like to hear from you. If your first language is not English, or you require a
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, Mathematics. Excellent English written and spoken communication skills. It is desirable that candidates possess expertise in some (but not all, or even most) of the following areas: Microbiology, Bacteriology