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Field
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-culture studies to evaluate mechanotransductive signalling. The resulting data will inform mathematical models linking material mechanics to biological responses, enabling the sustainable design of next
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their operational reliability. The PhD student will combine mathematical models, in-house laboratory tests in a wind-wave-current flume (https://research.ncl.ac.uk/amh/ ) and numerical methodology to quantify
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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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the execution of the project. The candidate(s) will undertake original research in AI-driven Financial Computing, within the School of Informatics in collaboration with School of Mathematics and the Centre
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a relevant subject (computer science, mathematics, or related subject) Proficiency in English (both oral and written) Python programming skills. Solid mathematical background is desirable. Studentship
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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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to oceanography and climate research communities. PERSON SPECIFICATION This project is suited for a candidate with a background in natural sciences, engineering or mathematics, with good numerical and programming
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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