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students to advance project goals. Provide technical guidance and mentoring on CFD, numerical methods, and high-performance computing workflows. 15% - Publication & Dissemination Prepare and submit
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provides excellent research computing resources (high-performance computing clusters, large-scale storage, and advanced visualization). Initial term: 2 years, renewable for a 3rd year contingent on
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, graduate, and undergraduate students to advance project goals. Provide technical guidance and mentoring on CFD, numerical methods, and high-performance computing workflows. 15% - Publication & Dissemination
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Carnegie Mellon University is a private, global research university that stands among the world’s most renowned education institutions. With ground-breaking brain science, path-breaking performances
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Data analysis experience, including AI and machine learning methods Interest in learning or experience with high performance computing Broad knowledge of college sports and/or elite-level competitive
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-Informed Neural Networks (PINNs) and geometric deep learning. Experience with active learning, agentic workflows, or other methods for autonomous experimentation. Familiarity with high-performance computing
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United States Application Deadline 24 Oct 2026 - 23:59 (America/Los_Angeles) Type of Contract Not Applicable Job Status Full-time Hours Per Week 40 Is the job funded through the EU Research Framework Programme
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technologies. The Pritykin lab (http://pritykinlab.princeton.edu ) develops computational methods for design and analysis of high-throughput functional genomic assays and perturbations, with a focus on multi
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, high-performance computing (HPC), and computational sciences. Major Duties/Responsibilities: Participate in: (1) design and implementation of scalable DL algorithms for atomistic materials modeling
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a diverse team of biological and chemical scientists Experience with high performance computing environment (HPC) / cluster job submission Knowledge of statistical methods, data science algorithms