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As Senior Computational Biologist, you will: Develop cutting-edge methods to predict which somatic mutations drive clonal expansion Integrate large-scale multimodal omic datasets from healthy and
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multimodality gastrointestinal, oncological, musculoskeletal and neurological imaging, as well as medical physics, statistical methodology, health economics, modelling, and health behaviour. The academic
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Fellow to join an exciting interdisciplinary research programme. This is a unique opportunity to investigate mechanisms of cancer dormancy and develop predictive models of late recurrence in oestrogen
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. Mathematics is the key to unlocking innovation and addressing these complexities. They all require new, predictive models that can link the processing and microstructure of formulated products to their final
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Improving the clinical success of porous orthopaedic designs – experimental and finite element study
musculoskeletal models and finite element analysis (FEA) models from clinical images and gait analysis data. The student will perform mechanical testing of the implants to validate the FEA models. The successful
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demonstration software, AI model training, and inference and prediction, and on the construction and maintenance of a visual language toolkit that supports the research collaboration and its dissemination
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posterior predictive checks, model comparison, programming in R (python/Matlab), implementations using R-packages rstan/JAGS and brms/STAN or equivalent interfaces. References Lages, M. A hierarchical signal
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We aim to predict the consequences of rapid environmental change such as that due to climate, habitat loss, renewable energy growth, pollution and over-exploitation of natural resources
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originate from molecular localisation defects in glia that contact the synapses. The project will use precision genetics methods in the Drosophila larval neuromuscular junction, a well establish model system
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, cost benefit and effectiveness analyses, risk and prediction modeling, data linkage and advanced meta-analysis. We have excellent engagement with government agencies, the NHS and local authorities, other