659 postdoc-in-thermal-network-of-the-physical-building Fellowship positions in United Kingdom
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This is an exciting opportunity for an experienced, highly motivated individual to join our vibrant, multidisciplinary rare disease research team. This postdoc will work within a multidisciplinary
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the UKRI Future Leaders Fellowship “AI-Driven Inference for Gravitational Waves: Accelerating Discoveries in Fundamental Physics” (PI: S Green). We believe that talented and inclusive teams deliver
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processes to recover the carbon fibre from carbon fibre waste. These carbon fibres can replace virgin carbon fibres with almost no loss in strength and the same electrical, thermal and corrosion- resistant
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(hiPSCs), cardiomyocytes, metabolism About the project We are recruiting a postdoc (established or newly graduated from their PhD) who has an exceptional ‘can-do’ attitude, with drive and enthusiasm to push
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responsibilities include: Generation of phenotype-specific networks from bulk-RNAseq and scRNAseq data from rare disease patients Building executable models (Boolean, ODE, agent-based or others) from omics data
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for studying mediation using longitudinal data exhibiting irregularity and informativeness of the visiting process. The work is motivated by the aim to find mediating mechanisms of cardiovascular disease in
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, statistics) and support researchers across the Faculty to build their computational skills. As Senior Bioinformatician, you will be responsible for maintaining reproducible, scalable workflows and for liaising
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. This project will use a range of wildtype, co-morbidity and tumour models to build preliminary data supporting a novel cardiac radio protecting drug, combining functional, histopathological, transcriptomic and
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research networks such as the Centre of Data and Statistical Science for Health (DASH) (https://www.lshtm.ac.uk/dash ) and the Multi-City Multi-Country Collaborative Research Network (https
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research networks such as the Centre of Data and Statistical Science for Health (DASH) (https://www.lshtm.ac.uk/dash ) and the Multi-City Multi-Country Collaborative Research Network (https