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project investigating mechanosensing in Diptera. This post will focus on using detailed wing geometry models and kinematic measurements in computational fluid and structural dynamics simulations to recover
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clinical endocrinology both paediatric and adult, genetic aspects and gene discovery in endocrine diseases, animal models, stem cells, signalling and cell biology. For further information visit: http
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regression models to complex forms of observational data, and of applying causal inference approaches to health data are essential. Experience of analysing time-to-event outcomes is desirable. This role offers
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responsibilities will include: Pre-registering data analysis plans; Leading and conducting advanced statistical analyses (e.g., twin/family designs, genomic and epidemiological methods, longitudinal modelling
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infrastructure enables recruitment of 200-300 severely injured patients annually as part of the ACIT study. We also have a well-established experimental modelling group with full ethical approvals in place for all
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clinical studies. They will also engage with project partners developing the AI-assisted tools and with evidence users to ensure that the evidence syntheses are fit for purpose and meet user needs. The post