642 parallel-computing-numerical-methods-"DTU" Fellowship positions in United Kingdom
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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the lead on, plan, develop and conduct individual and/or collaborative research objectives, projects and proposals either as an individual or as part of a broader programme. - To acquire, analyse
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Position Details School of Computer Science Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting salary is normally in the range £36,130 to £45,413 with potential
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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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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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Computer Science, Data Science, AI, or a related field with substantial expertise in data science/AI methods Strong publication record in relevant areas Demonstrated ability to work across disciplinary boundaries
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The objective of the post is to contribute the delivery of a collaborative project funded as part of the UKWIR Chemical Investigation Program 4 - Emerging Substances Endocrine Disruptors project
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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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modelling using Delt3D software. The role of the researcher is to perform physics-based modeling to build a numerical model that can predict storm surges in Singapore coastlines based on different weather
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treatment and reducing brain injuries Modern MRI scans tell us about a tumour’s biology. Through advanced computing (radiomics), it is possible to extract much more information from MRI images than is visible