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of the assembly of these complex microbial communities using ecological theory and mathematical models. The questions we address are: (1) how does the microbial community change during cultivation
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Partnership at the University of Cambridge. This programme is a collaboration between industry and academia, now in the final 24 months of a 60-month effort. The programme integrates research and innovation
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with a background in cognitive psychology, data science or computer science and a willingness to develop skills in computational models of cognitive processes, statistical methods, and programming (R
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Project Overview This PhD project is part of an Innovate UK-funded research programme focused on developing a novel ammonia-fueled engine and generator set (genset) demonstrator for harbour and
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environmental impacts of digital activities. You will lead projects modelling the energy usage of different computing equipment (personal computers, servers, High-Performance Computing infrastructure
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modelling for fast moving landslides: Hōretireti Whenua Sliding Lands ”. This research programme seeks to plan for, invest smartly, and reduce risk from landslides. This project aims to create, for the first
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the solution of governing PDEs. - Train machine learning models to predict lifetime and failure based on loading and environmental histories. The PhD student will have access to world-class computing facilities
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sources such as (i) atmospheric models, (ii) satellite remote sensing, (iii) land use information, and (iv) meteorological data. The aim of this PhD is to develop and implement models for integrating data
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an independent impact assessment of potential climate interventions in the Arctic marine environment through laboratory experiments and computer modelling. The team will develop physical, climate and ecosystem
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determine the impact of community acquired pneumonia that requires hospitalisation has on the quality of life of patients. The final stage will be to design a generic economic model to evaluate any new