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to register an account with our recruitment system (if you have not already) and apply online. Applicants must have (or be close to obtaining) a PhD. Appointment at Research Associate level is dependent
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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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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 Innovation Associate to join this ambitious project. You should hold a PhD in a relevant field such as applied/pure mathematics or physics and have an established track record of original research
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to develop and improve current simulation methods (quantum and classical) to study such systems. The overarching aim of the post-doctoral position is to develop and apply computational approaches that enable
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on the genetics of appetite and obesity. Candidates should be of postdoctoral level with relevant experience of canine or/and human genomics, or molecular biology. Candidates without PhD but significant expertise
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Associate will be expected to support and maintain the Department's and University's national and international reputation for excellence in teaching. You will have relevant teaching experience, hold a PhD in
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to take a leading role in advancing both research and pedagogy in Latin Studies in Cambridge, and in promoting the field of Classics as a whole within the UK and internationally. They will hold a PhD or
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in any one year, 80 MPhil students and 80 PhD students. Further particulars can be downloaded from the link below. Closing date for applications is 10 July 2025. Interviews will be held on Thursday 17
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://www.mmll.cam.ac.uk/ Candidates will need to show evidence of the following qualifications, skills and experience: A PhD in a relevant subject area (or clear evidence that completion of the PhD is imminent); Fluent