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engineering or a related discipline. Strong analytical, problem-solving, communication, and teamworking skills, along with experience in computational modelling are essential for the role. What we offer: - A
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data acquisition and interpretation are highly desirable. This is a collaborative project between the School of Pharmacy, The School of Computer Science, Physics and Astronomy, the School of Life
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and knowledgeable in the areas of stress analysis (including the Finite Element Method), material characterisation (particularly flow stress determination and modelling), mechanical testing methods
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Facility at the University of Nottingham. The Facility is operated jointly by the Schools of Chemistry, Life Sciences, and Physics and Astronomy and comprises a 600 MHz DNP MAS NMR spectrometer equipped with
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(MASI)” involving four UK universities (Nottingham, Cardiff, Cambridge, and Birmingham) and join the Computational Materials Science group led by Prof. Elena Besley (https://ebesley.chem.nottingham.ac.uk
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relevant subject area; Excellent communication, presentation and writing skills in English; Proficiency in laboratory techniques and analytical methods relevant to catalysis and material sciences; Extensive
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team consists of researchers across sustainability, food systems, operations and supply chain management, computer science, environmental and animal science, and environmental statistics. The successful
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, the role holder will work with the academics, researchers and PhD students in managing and conducting research activities across the programme. Prior direct experience of successful PhD student supervision