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, engineering, materials science, maths, or computer science), or equivalent experience Experience with uncertainty quantification or error analysis Familiarity with numerical methods (e.g., Monte Carlo, Finite
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or a numerate discipline OR equivalent experience. Broad knowledge of probabilistic models, Bayesian inference and machine learning methods. Good knowledge of R, Python or both (links to project source
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of new EEG and MEG neuroimaging and mc-tCS simulation approaches based on realistic head volume conductor models using modern finite element methods as well as sensitivity analysis. The new methods will be
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neuroimaging and mc-tCS simulation approaches based on realistic head volume conductor models using modern finite element methods as well as sensitivity analysis. The new methods will be applied in close
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. Demonstrate sufficient breadth and depth of specialist knowledge in the discipline and of research methods and techniques to work within established research programmes. Show a proven ability to communicate
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of Ultra Efficient technologies to cut fuel burn and weight, independent of the fuel choice, for a new high build rate product using wing-span as a key enabler. Development of experimental test methods
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of recycled aluminium. More specifically, the project will focus on advanced numerical methods to understand how defects and different microstructures affect the strength of mega-cast components. As a PhD
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). The Bokulich laboratory develops bioinformatics methods and software for microbiome research, including QIIME 2, and applies these tools to study microbiomes at the interfaces of foods and human health. Job
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and mentor junior researchers in laboratory methods, data analysis, and academic writing. - Strong collaboration and communication skills, with a track record of working across disciplinary boundaries
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, or a closely related field with expertise in one or more of the following areas: Finite element methods for partial differential equations Multiscale numerical methods Flow and transport in porous