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for a further 6 months once in post. For more information: Prof Eric Robinson, eric.robinson@liv.ac.uk If you are still awaiting your PhD to be awarded you will be appointed at Grade 6, spine point 30
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
, epidemiology, and socio-environmental modelling. To be considered a successful candidate; A PhD degree in Ecology, Biodiversity analyses, Environmental Science, Remote Sensing, Epidemiology, Data Science, or a
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this role, we are looking for candidates to have the following skills & experience: Essential criteria PhD, or in the final stages of obtaining a PhD, in a relevant area of social science (e.g., sociology
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Engineering, Science and Theory (NESTiD) Scientific Computing (SciComp) Vision, Imaging and Visualisation (VIViD) We are ranked 4th in the UK in the Complete University Guide 2024. For more information, please visit our
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interest in infectious disease epidemiology are essential for the post. For appointment to Research Associate, you should hold a PhD in infectious disease epidemiology, evolutionary biology, bioinformatics
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inference attacks, to mitigate privacy leaks in MMFM. You will hold a PhD/DPhil (or be near completion) in a relevant discipline such as computer science, data science, statistics or mathematics; expertise in
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computer codes to solve some of the daily research problems and have experience with high performance computing. You should have a PhD in Chemistry, Physics or Materials Science with a proven research track
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, three PhD students and a postdoctoral researcher. The project is led by Dr. Yiren Zhao at Imperial College, who is supported by Prof. George Constantinides and Prof. Wayne Luk. The team also includes Dr
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be about to obtain) a PhD in chemical biology. They will be highly motivated and able to work independently. Excellent organisational and interpersonal skills are required to ensure success in liaising
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have proven academic ability and a demonstrable high level of technical competence in computational data science and the analysis / modelling of the results. Theoretical or experimental experience of in