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consist of incorporating our physical findings into the GlaDS model by representing a distributed drainage system in which conduits and cavities are connected in series. The candidate will be required 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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programmers and can target different hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a given Tiramisu program, many
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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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wide range of research and teaching interests, with priority given to: cybersecurity, artificial intelligence, systems (including embedded, distributed, parallel, and high-performance), software
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engineering workflows for data analysis and decision support. These workflows require distributed parallel computing, utilizing both cloud and on-premise high-performance computing (HPC) resources
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-K0063) Knowledge of parallel and distributed computing concepts. 19. (NICE-K0070) Knowledge of system and application security threats and vulnerabilities (e.g., buffer overflow, mobile code, cross