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Field
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to develop long term, quantitative strategic plans that emphasize sustainable agribusiness enhancement. This PhD position is carried out in collaboration with the Doctoral Program in Agricultural and Forestry
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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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science (for example, but not limited to, data science, machine learning, statistics, computer science, mathematics, etc.) acceptance by a PhD supervisor with examination admission for PDS and formation
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, mathematics, engineering, computer science, or related subject) Proficiency in English (both oral and written). Knowledge in cryptography is desirable. Studentship and eligibility This studentship is suitable
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students on the campus, offering the chance to engage and connect - our PhD Representatives offer information and advice when needed access to high-performance computing a chance to contribute meaningfully
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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
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Deadline: 31 August 2025 A fully funded 3.5 year PhD position is available to work on the project titled “Scalable benchmarking for digital quantum computers based on blind testing”. This position
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to develop long term, quantitative strategic plans that emphasize sustainable agribusiness enhancement.This PhD position is carried out in collaboration with the Doctoral Program in Agricultural and Forestry
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suitable to candidates with a wide range of backgrounds such as but are not limited to: climate science, psychology, mathematics, geography, environmental science, law, computer science, public health
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writing and presentation skills. At the start of the PhD, having obtained a Master’s degree in a relevant field, such as AI, mathematics, physics, (computational) neuroscience, etc.. Terms and conditions