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Engineering undertakes research across geotechnical engineering; structures and fluids; resilient systems and climate action; and railway engineering, while working closely with other research groups across
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Resilience Forums, addressing the following questions: How do statutory duties, governance and accountability structures, and partnership dynamics shape emergency planning, response and recovery? What
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candidates will be involved in projects exploring novel ways to incorporate topological structures into deep learning pipelines, contributing to both theoretical advancements and practical applications
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will lead the experimental characterization of a novel, disruptive dialyser design. Directly supervised by Dr. Melika Gul, you will be responsible for the design, construction, and testing of a scaled-up
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. Applications are encouraged from candidates with experimental backgrounds in physics, material science, biophysics, structural biology or related disciplines with an interest and experience of advanced EM
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should have an aptitude for semi-independent laboratory work, which is well supported by the dynamic academic structure of the department. The candidate will also have the opportunity to work with
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concentrates on understanding complex data structures, investigating mismatches, identifying root causes of data issues and resolving them. You will: Analyse source and target system databases to understand how
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, material science, biophysics, structural biology or related disciplines with an interest and experience of advanced EM methods. You will have access to state-of-the-art instrumentation, including: a double
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Facility Scientist, you will contribute to all aspects of model generation and validation. Responsibilities will include: • Design and construction of molecular reagents and targeting constructs
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, computational biology, structural biology, biophysics, pharmacology or related discipline. Significant experience in virtual screening and molecular docking. Experience with machine learning/AI approaches in drug