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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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and classifying material, and visualization methods. Candidates should possess a PhD in a field relevant to the interface of energy technology, economics, data science and public policy. Please see the
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(or be about to obtain) a PhD in a relevant area. The ability to work both as part of a team, and independently, coupled with excellent communication, organisational and problem-solving skills are required
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have or be about to receive a PhD in immunology, and be able to demonstrate the following skills: Mouse experimental procedures, tissue processing, isolation and phenotyping/manipulation of cells using
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an associated Masters, or ideally PhD, qualification. - Experience of processing and analysing large biological datasets. - Expertise in programming using at least one of R or Python. - Experience in
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through its research outputs, including publishing impactful research in internationally recognised Finance journals as well as placing its PhD graduates in academic careers. The ideal candidates will have
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. They will use this knowledge to develop strategies to engineer expression in plants, seeking to optimise yields from metabolic pathways. Key skills The successful candidate must have a PhD in molecular or
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deliver end-to-end genome engineering projects, but also to identify opportunities where an AI-first approach would add maximal value. Minimum Requirements: A PhD or other relevant qualification
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external research funding and supervision of PhD students to completion. The appointee will also have the ability to manage and develop effective working relationships with research staff and display a
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to the Master’s PA, Debbie Brown, at Selection Criteria Applicants must 1. have been awarded their PhD at the time of application. 2. be in an established post-doctoral position normally within the University. 3