610 postdoc-computational-fluid-dynamics-"Prof" Fellowship positions in United Kingdom
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challenges from low carbon shipping and sustainable fuels to solar power technologies and advanced brain models. Learn more at https://mecheng.ucl.ac.uk . Within this dynamic environment, the Moazen Lab is
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will help with the development of proteomic techniques that simultaneously study brain tissue and biological fluids and with the analysis and integration of omic data to identify novel biomarkers for ALS
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recently funded 5-year programme of antifungal drug discovery at the MRC Centre for Medical Mycology. This exciting new programme connects MRC CMM researchers with drug discovery experts and scientists from
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materials, notably wear, fretting, and thermo-mechanical fatigue. Experimental studies to support these modelling activities are also of great interest to the group. Visualisation of multiphase fluids with
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innovative, well-organised, dynamic and promising individuals who are motivated to further develop their career. The fellowship supports salary (equivalent to Band 6 NHS), PhD fees (UK level), and research
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The MRC Centre for Medical Mycology (MRC CMM) seeks an experienced assay development scientist to join a recently funded 5-year programme of antifungal drug discovery at the MRC Centre for Medical
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us to build/learn generative, probabilistic forward models of users and their physical and computational environments. This will involve modelling sensors, developing dynamic models for control and
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simulations using ENVImet and dynamic thermal modelling to study how physical parameters and microclimate of the playground impact on children’s thermal comfort and to evaluate the potential impact of
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an exciting opportunity to contribute to the ESRC Education Research Programme . The programme is committed to resetting the terms under which education research, policy and practice interact in the interest
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selected candidates. This is a high-impact role with the potential to shape the future of rare disease research. Join us to push the boundaries of what’s possible in computational biology and personalised