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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging
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Master in Epidemiology or Public Health with experience in medical statistical analyses, an understanding of Health Economics, knowledge of the strengths and weaknesses of scientific research, excellent
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scope to define the project during the first year of study in line with their own research background and interests. Applications are sought from people with either a social science master’s level degree
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for An enthusiastic, self-motivated, and resourceful candidate with a 1st or upper 2:1 degree in mechanical engineering, aerospace engineering, materials science, electrical engineering, or a related field. Desirable
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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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suitable for a hard-working researcher with an interest in respiratory infections. Essential skills: A BSc degree or equivalent ideally in a health related field, excellent computer literacy, good inter
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second) in maths, physics, computer science, electrical and electronic engineering, mechanical engineering or social science disciplines looking for a challenging research project in an interdisciplinary
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research programme funded by the Academy of Medical Sciences Springboard award. This project aims to explore the role of these neighbouring glycoproteins in neurotrophin-mediated neuronal development as
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(School of Computer Science) External Partner: Build Test Solutions Ltd (BTS) Start Date: 1st October 2025 Eligibility: Home students only | Minimum 2:1 in a relevant discipline Stipend: Home students only
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should have a strong mathematical background, particularly in dynamical systems theory, and a keen interest in network science, and scientific computation. The student will gain invaluable experience