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deterioration driven by environmental cycles | Postgraduate study | Loughborough UniversityThis PhD project aims to advance understanding of how environmental (weather) cycles drive deterioration in geomaterials
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Trust. The successful candidate will work closely with the PI and a PhD student within a larger cross-disciplinary team to construct a quantitative computational model of carbonate biomineralisation
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publications, presenting at conferences, and engaging with stakeholders. There is also the opportunity for a part-funded PhD studentship (Tuition Waiver) as part of this position, subject to final approval
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progression to PhD depending on performance during the initial period. Main duties and responsibilities Admin - ordering consumables, tracking cost and use of consumables PIL training - opportunity to acquire a
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integrated with the NiMARE (NMA) software project. To be considered you will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain
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on neuroimaging meta-analysis (NMA), developing novel methods and implementing them in efficient, well-documented and user-friendly code to be integrated with the NiMARE (NMA) software project. To be considered you
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PhD (research associate) or (under)graduate degree (research assistant) in neuroscience, biology, engineering, or other relevant disciplines. We are looking for someone with previous experience in
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bioprocessing technologies to deliver efficient pathways for upcycling captured carbon into high value products. The successful candidate will have a PhD, or be studying towards a PhD, in synthetic biology or a
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our software development team, developing novel scientific algorithms and applications in the areas of spectroscopic analysis and mining of the science data catalogues extracted from the pipelines
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, and 2) to develop a physical model of cell shape dynamics during EMT. You should hold a PhD (or about to be awarded a PhD) in Biophysics or a related field and have extensive experience with cell and