626 parallel-computing-numerical-methods-"DTU" Fellowship research jobs in United Kingdom
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administrative processes. Possess sufficient breadth and depth of specialist knowledge in Health & Social Care research methods and techniques to work within SUMIT programme. To be successful at shortlisting stage
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equivalent) in a quantitative scientific field (e.g. climate science, meteorology, physics, maths, or computer science), be a nationally recognised authority in areas of climate or Earth system research, and
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, with opportunities to build an international research portfolio. The post holder will work on developing and testing study design and data analysis methods, particularly related to cluster randomised
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from the traditional chemicals industry to pharmaceuticals and personal care products. About this Modelling Role This post-doctoral role seeks to advance the systems modelling methods of microbial cells
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opportunity for an enthusiastic and motivated postdoctoral fellow in data-sciences and biomedical informatics to work on exciting human and veterinary health studies, such as the identification of novel
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collaborative research environment that exemplifies IDAI's distinct approach to interdisciplinary data science and AI research. Person Specification PhD (or near completion) in Computer Science, Data Science, AI
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related field, possessing a developing research profile and the ability to implement novel statistical methods using various computing programs. You may also: Have completed a PhD in statistics, applied
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strategic capability within the UKERC consortium, overseeing the development of UKERC outputs on electricity markets and policy, undertaking and leading modelling and numerical analysis as appropriate. You
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August 2025 Background To create and contribute to the creation of knowledge by undertaking advanced analysis and validation experiments within the MRC BioFlare research programme: Although outcomes in RA
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spectroscopic data analysis. This role forms part of a larger research effort exploring advanced polymer processing techniques and data driven methods to improve material performance and manufacturing efficiency