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About the role The main purpose of this position is to lead the computational and mathematical aspects of a BBSRC-funded project focused on engineering robust, modular, synthetic microbial
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PhD in Mechanical Engineering, Aerospace Engineering, Civil Engineering, Biomedical Engineering, Mathematics, Physics, Computational Mechanics/Engineering or related discipline. (Thesis submitted by
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interviews will be arranged for early October. About you The successful applicant will have a PhD in electronic engineering, physics, or a related subject. The applicant will have experience in designing
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Essential: PhD (or near completion) in Chemical Engineering, Environmental Engineering, Sustainable Process Engineering, or a closely related field. Demonstrated experience in techno-economic assessment and
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of Engineering at the University of Nottingham. The position is part of a larger project in collaboration with the School of Chemistry and you will work in a highly collaborative and interdisciplinary team
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Magnini in the Faculty of Engineering at the University of Nottingham. The position is part of a larger project in collaboration with the School of Chemistry and you will work in a highly collaborative and
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Requirements Essential: • PhD (or near completion) in Chemical Engineering, Environmental Engineering, Sustainable Process Engineering, or a closely related field. • Demonstrated experience in techno
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Requirements Essential: • PhD (or near completion) in Chemical Engineering, Environmental Engineering, Sustainable Process Engineering, or a closely related field. • Demonstrated experience in techno
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development of the National Facility for Ultra-High Field (11.7T) human MRI/S at the University of Nottingham. We are looking to recruit MR physicists and biomedical engineers, or equivalent, enthusiastic
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of publications. Criteria Essential or desirable Stage(s) assessed at A PhD (or close to completion of a PhD) in Machine Learning or a similar area (e.g. in Computer Science, Electrical and Electronic Engineering