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partners. Training & environment You’ll gain deep skills in hypersonic flows, AI for PDEs, data assimilation, and reproducible HPC workflows (Python/C++/PyTorch/JAX). You’ll be supported with paper writing
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proficiency in three of the items in the following list: - Fluent programmer (e.g., python or other) - Fundamental of finite element analysis and experience with FEA software
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Engineering or Computer Science. We would also like to see experience in: Machine Learning, Optimisation, Python, finite elements How to apply: Stage 1: Submit your 2-page curriculum vitae (CV), transcripts and
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predictive checking, model comparison) • Computational modelling with Python and Dynesty, JAX, NumPyro, and PyTorch • Use of asteroseismic and spectroscopic survey data (e.g. PLATO, Gaia, APOGEE, TESS) • High
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related subject Previous coding experience (e.g. python, bash, matlab) Good administrative skills, and the ability to organise and prioritise workload Excellent interpersonal, oral and written communication
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. python, bash, matlab) Good administrative skills, and the ability to organise and prioritise workload Excellent interpersonal, oral and written communication skills Ability to work independently and as
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analysis and programming skills (e.g., Python, MATLAB, or similar) Strong motivation, good communication skills, and the ability to work both independently and as part of a team Proficiency in English
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or Python. Working with the workstream Co-leads and wider research team, they will contribute to analyses, publications, reports and dissemination, as well as undertake administrative tasks and present
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(e.g. APMS) with software such as Stata, R, MPLUS, or Python. The successful candidate will contribute to publications, reports and dissemination activities, present findings at seminars, meetings and
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Python with demonstrable familiarity with PyTorch, experience in working on shared codebases, excellent applied math skills (especially probability theory, matrix algebra, calculus). Beyond technical