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Field
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computational modelling of additive manufacturing and develop high-performance GPU-based CFD solvers. Qualifications • With PhD degree • Strong research experience in developing GPU-based
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compensation and working conditions. Basic Qualifications Ph.D. or M.D./Ph.D. in areas such as machine learning, computer science or closely related field. Excellent programming skills and practical experience
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. The successful candidate will be expected to teach across the curriculum, including introductory courses within their expertise, and to build an externally funded research program that complements the department’s
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port scientific applications to maximize performance across CPU, GPU, memory, storage, and I/O. Contribute technical expertise to faculty projects through the RCC Consultant Partnership Program and other
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with
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department currently manages a SLURM-based cluster comprising CPU, high-memory (HMEM), and GPU nodes, supporting a diverse range of computational research. About the role As the Institute’s computational
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you will operate what you design. We expect and support open-sourcing and publishing this work. The environment A large NVIDIA GPU cluster (B300/H200/H100 class) running self-hosted open-weight models
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GPUs (e.g., B200, RTX 6000 Blackwell Pro, H200) and CPU architectures that, even if they increase complexity, generate the kinds of problems we love! This role in our Operations Team provides support for
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Systems and Software Program (WASP ). You can find more information about us on the Department of Information Technology website. The position is hosted by the Division of Scientific Computing (TDB), one
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/scientific computing and numerical methods for PDEs High‑performance computing (parallel distributed programming, GPU programming) Astrophysical fluid dynamics and/or magnetohydrodynamics Radiative transfer in