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background in at least one of the following areas: Biomedical Engineering, Biomedical Informatics, Biostatistics, Computer Science, Electrical and Computer Engineering, Mathematics, or a related field. The
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impairment across tissues and brain regions. The ideal candidate will have a quantitative background (bioinformatics, computational biology, biostatistics, statistics, computer science, or applied mathematics
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master's degree in agricultural or environmental economics, applied mathematics, or a related fieldGood background in bio-economic modelling, CGE modelling, and optimization techniquesExperience with
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
, applied mathematics, or a relevant engineering discipline Good programming skills and experience with numerical modeling Interest in performing experiments Excellent written and spoken English skills High
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master’s degree or diploma in physics, applied mathematics, or a relevant engineering discipline Good programming skills and experience with numerical modeling Interest in performing experiments Excellent
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at the Masters and PhD level develop and strengthen teaching and mentorship experience Applicants must have, or be about to obtain, a PhD (or equivalent) in applied mathematics, physics, engineering, or a related
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focus on using applied mathematics and AI methods to address real-world challenges. What we’re looking for You will hold a PhD in mathematics or a related discipline and be able to demonstrate previous
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This new post is available from 1 August 2025 on a fixed-term basis until 23 June 2026. The post We seek to recruit a new full-time Postdoctoral Research Associate or Fellow to use mathematical
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About the role We are seeking a Teaching Fellow in Engineering Mathematics and Computational Methods to support in the delivery of our education programme in the School of Engineering. The School
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Physics, Chemistry, Applied Mathematics, or related fields. Desirable: Fluent English, spoken and written Strong background in computational Physics and Statistical Physics Previous work experience in