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opportunity for a highly motivated and skilled Research Associate/Assistant in statistics to join the EPSRC funded project PINCODE: Pooling INference and COmbining Distributions Exactly: A Bayesian Approach
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expertise or additional resource for a project.) You will contribute to a programme of research, funded by the Horne Family Charitable Trust, which aims to increase the evidence base on Domestic Violence and
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machine learning. The position will involve working with different research groups in the Department of Computer Science at the University of Cambridge, UK. In this collaborative project, we will apply
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. The Role This is an exciting opportunity for a highly motivated and skilled Research Associate/Assistant in statistics to join the EPSRC funded project PINCODE: Pooling INference and COmbining Distributions
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, developing solutions for removing and storing greenhouse gases into the built environment, and developing the life cycle assessment method for quantifying multiple cycles of using building products. Your role
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and modelling of African malaria vectors and malaria transmission F2 Experience working with multiple partners either in academia or in malaria endemic countries F3 An emerging national or international
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services research and epidemiology, along with practical skills in managing large, complex datasets. Proficiency in statistical software, especially STATA, is essential. You must be able to handle multiple
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framework to accommodate new components like EV chargers and distributed generation, and you will apply these insights to both large-signal and small-signal stability analyses. Working closely with academic
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like EV chargers and distributed generation, and you will apply these insights to both large-signal and small-signal stability analyses. Working closely with academic and industrial partners, you will
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Full-time: 35 hours per week Open-ended (permanent)/Fixed term: 31 August 2026 The project is looking to recruit research assistant(s) familiar in AI, NLP and financial computing to assist with