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of computational and applied mathematics, including but not limited to data-driven numerical modeling, scientific machine learning and AI for science and engineering, computational uncertainty quantification
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application of advanced artificial intelligence, data-driven modelling approaches and to understand, predict and help control the emergence and spread of diarrhoeal diseases and antimicrobial resistance
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knowledge of III-V semiconductor-laser physics and design, such as Fabry-Perot, DFB, DBR or external-cavity lasers. You have experience with numerical modelling of optical components, using custom code
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couplings, this project will seek to further the fundamental understanding the wear behaviour of such components through both experimental and numerical studies. Experimental work will be carried out using a
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community-based, distributed model of education, which fosters inclusion, discovery, and innovation. Hybrid work options up to 2 days per week may be available after 6 months of successful employment
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 19 days ago
-sensitive modeling, high-fidelity experimental characterization, and uncertainty quantification capabilities for metallic aerospace materials, with emphasis on additively manufactured (AM) metals
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to the mathematics of plasmas, with a focus on kinetic theory and PDEs. - Specific topics include stability, long-time behaviour, and mathematical properties of magnetised plasma models (such as magnetized
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-Soma to explore the occurrence of water worlds and to characterise their properties, both observationally and by developing models of their atmospheres. Start date is flexible, from early 2027 onwards
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additive manufacturing. The role will focus on thermal field modelling, multi-physics numerical simulations, machine learning and process parameter optimization. We expect the candidate to use data-efficient
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and spoken English. Knowledge of Czech is not required. Experience in one or more of the following areas would be an advantage: gravitational-wave modelling; numerical relativity; cosmological data