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Field
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foundation models, 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
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community and the general public in the Denver metropolitan area. The current strengths of the faculty are in the areas of algorithms, artificial intelligence, computer networks, graphics, parallel and
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-time Hours Per Week 37h15 Offer Starting Date 26 Oct 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a
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December 2032. About Us The ML Cloud team designs, runs and safeguards high-performance computing infrastructure tailored to machine learning workloads. Our state of the art systems are distributed across
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of the group. Strong knowledge of performance modeling, simulation, and benchmarking of parallel and distributed computing systems and of the workflow systems that run on them. Familiarity with the FAIR data and
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and parallelization of scientific simulation codes. In research in theoretical or computational quantum physics. In the development and application of Quantum Monte Carlo methods. Having worked
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development skills; distributed or parallel computing is a plus. Experience designing and executing field experiments in urban or environmental settings, with willingness to engage in fieldwork in dense urban
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and Product Development, where multiple externally funded research projects are conducted in parallel in close collaboration with industry, public authorities, and international partners.The successful
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administration (OpenHPC, Redhat Enterprise 7/8, CentOS 7/8/Stream, Ubuntu), experience with SELinux is a plus Parallel and distributed file system (Lustre) experience is a plus, as well as knowledge of Ceph
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, parallel or distributed file systems, cluster management, artificial intelligence tools and techniques, performance engineering, benchmarking and capacity planning. Advanced experience designing and