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corresponding numerical methods in computer codes. Experience with numerical methods for solving partial differential equations such as finite difference, finite element, and/or spectral methods. Ability to
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corresponding numerical methods in computer codes. Experience with numerical methods for solving partial differential equations such as finite difference, finite element, and/or spectral methods. Ability to
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, computational science, or closely related). Relevant coursework (examples): Computational physics/scientific computing and numerical methods for PDEs High‑performance computing (parallel distributed
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NTNU Norwegian University of Science and Technology | Trondheim, Sor-Trondelag | Norway | 23 days ago
academia. Your immediate leader will be the head of the computing unit. About the project The primary research goal will be to create quantitative performance models that describe a range of numerical
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-machine learning approach based on the following key steps. It is expected that such combination will improve computational efficiency compared to traditional numerical methods maintaining high level
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-network surrogate models, physics-informed neural networks, uncertainty quantification, or digital-twin development. High-performance computing and parallel numerical workflows. Terms of Appointment
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coursework (examples): Computational physics/scientific computing and numerical methods for PDEs High‑performance computing (parallel distributed programming, GPU programming) Astrophysical fluid dynamics
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modeling, including numerical analysis, finite element methods, and software engineering Experience in software development in the C++ and Python languages The ability to work flexible hours and travel
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Sensitivity studies Validation activities Expertise in computational modeling, including numerical analysis, finite element methods, and software engineering Experience in software development in the C
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scale Demonstrated experience conducting simulations on high-performance computing clusters, including scheduling systems, parallel scaling and the management of large numbers of concurrent jobs