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Field
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define observable events based on expert knowledge and available evidence. Development of a post-race analysis structure, process and data ‘toolkit’ that can build on historical understanding of race
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, engineering, physical sciences, economics or any other field where evidence is provided of sufficient computing and mathematical background) solid experience of programming, machine learning methods and ideally
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, Physical Sciences, Computer Science & Maths): These are fellowships for women scientist and engineers. The candidates must be from eligible low and middle-income countries (find the complete list here: https
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overall, 6 in each category). Acceptable first degree: Computer Science/Physics/Maths or other numerate discipline. Mode of Study Full-time Start Date 1 October 2026 Funding Information ARIES studentships
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a first or upper second (2.1) class Master's degree (or equivalent) in chemistry, physics, materials science, computer science or other related discipline. Candidates with strong BSc (Hons) degrees in
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. Development of novel processing techniques Modelling techniques that can inform the direction of experimental activity Physical, mechanical and materials characterisation techniques Data-driven approaches
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PhD in Quantum Error Correction and its Applications School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Yingkai Ouyang, Dr P Kok Application Deadline: 15 January 2026
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observations and modelling of the physics and biogeochemistry of Antarctic shelf seas. You will gain experience in computer coding, statistics for environmental science, working with and piloting autonomous
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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a relevant subject (physics, mathematics, engineering, computer science, or related subject) Proficiency in English (both oral and written) A strong background in computer science, artificial