641 parallel-computing-numerical-methods-"DTU" Fellowship positions in United Kingdom
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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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to work with modern massively-parallel simulation codes. Candidates must have (or be close to completion of) a PhD in astrophysics or a related subject, and a BSc/MPhys (or equivalent) degree in physics
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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 trial designs and
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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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Evaluation (CMHPE), utilising their mixed methods their mixed-methods (ideally qualitative and quantitative) expertise. The role includes planning, coordinating, executing, and reporting on evaluation and
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which you will be encouraged and supported to use your initiative and creativity to identify areas for research, develop research methods and extend your research portfolio. In particular, focus
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, and improve linkages between atmospheric chemistry and public health research. The position is part-time and will require close interaction with parallel research activities at the University
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modelling and computer simulation to study the earliest stages of embryogenesis in mammals. This full-time post in the group of Dr David Richards at the Living Systems Institute (http://projects.exeter.ac.uk
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, specifically modelling burrowing behaviour and its impact on the skull. Responsibilities include conducting a range of computer simulations using discrete element and finite element methods, as
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with career stage). Essential Interview / Application / Test In-depth knowledge of Computational Intelligence/Machine Learning systems and methods, in particular those relevant to Explainable AI, Physics