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for example synchrotron based experiments. More information on these facilities can be found; There will be many rewards: Working as part of a large and experienced team across the cohorts will ensure a
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to test data, which are therefore only useable within a narrow range of scenarios. These limitations result in the requirement of large number of high-cost experiments being conducted to populate the models
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, manipulate large datasets, visualise data and perform numerical and statistical analysis is a requirement. Experience in handling 'big data', machine learning and working in distributed teams, is useful
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local extinction of large-bodied frugivorous birds and mammals, leaving structurally intact yet defaunated forests missing key ecological functions like seed dispersal for large-seeded plants. Studying
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discipline that combines multiple data sources along the patient pathways and develops real-world evidence to inform future clinical practice. The project will involve developing novel methods such as
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scattering, and rheometry will be conducted to understand the dynamics and interactions between ingredients in the liquid formulation. This information will be correlated with atomic force and electron
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quantitative and qualitative data. This project is likely to involve undertaking a systematic review; interrogating and analysing large-scale healthcare datasets; and using qualitative methods, such as
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of the research findings. Person Specification Candidates will be expected to have a first degree in Economics or proximate fields; strong analytical skills; experience in quantitative data analysis using large
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and preventing future losses, but their use remains limited. This project aims to use whole genome sequence (WGS) data from museum samples of Mazarine Blue and Large Copper butterflies to conduct a
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exposure and vulnerability to buildings, infrastructure, and people. This exciting PhD project aims to harness the latest developments in high-performance numerical models and data analytics technologies