643 parallel-computing-numerical-methods-"DTU" Fellowship research jobs in United Kingdom
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Research Fellow (Fusion Shielding Materials) - School of Metallurgy and Materials - 105638 - Grade 7
variety of research methods, such as scientific experimentation, literature reviews. Analyse and interpret data Contribute to developing new models, techniques and methods Disseminating research results
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refine their design as they progress. We will work closely with co-investigators from the Ifakara Health Institute (Tanzania) to ensure the methods are feasible and implementable in disease-endemic
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(CMHPE), utilising their mixed methods their mixed-methods (ideally qualitative and quantitative) expertise. The role includes planning, coordinating, executing, and reporting on evaluation and improvement
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related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research
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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics
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science, and a vivid interest on digital democracy, in particular, the areas of computational social choice (voting methods), deliberation and collective decision making. You will know how to work with data
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capability Fluency in relevant models, techniques or methods and ability to contribute to developing new ones High level of competence in computer programming, with C++ an advantage. Ability to communicate
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of a PhD. • Expert knowledge of linear PDEs (in particular wave equations and elliptic equations), high-frequency asymptotics, and numerical methods. • Excellent communication and organisational
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collaboration with the world-leading Briscoe lab at the Francis Crick Institute. It is using mathematical and machine-learning methods to study the early development of the neural system and developing those
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(STFC, Daresbury), Prof. Jonathan Tennyson (University College London) and Prof Michael Charlton (Swansea). The Research Fellow will work on the development of methods and computer programs adapted