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MOHAMED BIN ZAYED UNIVERSITY OF ARTIFICIAL INTELLIGENCE | Dhabi Kalan, Haryana | India | about 2 months ago
, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM datasets in the
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, computational resources, robustness, and adaptability matter alongside conventional accuracy measures? Depending on the research direction, the work may range from low-level GPU and systems optimisation to
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diagrams, technical specifications, design packages, bills of material, capacity models, implementation strategies, and technology roadmaps. Evaluate CPU, GPU, accelerator, memory, interconnect, storage
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massively parallel computing systems, including GPU-accelerated platforms. Develop and maintain scientific software, primarily in Python , using modern practices for software development, testing
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matching, diffusion), simulation-based inference, and robust and active learning. The group has a wide network of collaborators and strong access to compute through national GPU systems (NAISS, e.g
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promising habitable exoplanets around solar-like magnetically active stars? Join us to build next‑generation GPU‑accelerated models of stellar dynamos and connect them to exoplanet discovery and space
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related infrastructure. Oversees day-to-day reliability and long-term evolution of clustered compute, GPU resources, high-performance storage, and the scheduler/tooling that support research at scale
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experience with HPC environments: job schedulers such as Slurm, shared filesystems, and multi-node GPU systems Strong Linux systems and container skills (Docker/Podman and HPC runtimes such as enroot or
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research infrastructure partners to deliver innovative bioinformatics solutions across high-performance computing, GPU and cloud environments. Through the development of shared tools and services, specialist
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schedule. You Will: Set and drive the technical roadmap for AI-enabled research computing, including GPU and accelerator capacity planning, containerized and AI workflows, and MLOps tooling. Anticipate