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Field
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learning, or optimization Strong programming skills in Python and experience with scientific computing and machine-learning libraries Ability to work across experimental, robotic, and computational systems
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discoveries in protein function, ligand binding, and dynamics through scalable computational analysis. The ideal candidate would have a background and an interest in Computational Biology, Artificial
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 27 days ago
, and create personal and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our vision is to be
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-source modeling and collaborative research. The successful applicant will play a central role in developing and applying Tools for Energy Model Optimization and Analysis (Temoa), a widely used open-source
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translational diagnostics. This position combines wet-lab and computational research, with opportunities to lead projects, develop new methods, publish first-author work, and collaborate across academic, clinical
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-throughput data, identify differentially expressed genes, explore protein interaction networks, and perform pathway and functional enrichment analyses. Responsibilities also include developing and optimizing
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' postdoctoral fellows as part of the JAX/Roux Institute joint Applied Data Science Postdoctoral Fellowship program. Under this program, postdoctoral trainees will be co-mentored by NU and JAX researchers working
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modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The candidate is expected
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The Geeleher Lab tightly integrates computational/AI-based analysis of high-throughput genomics datasets (e.g. single-cell / spatial genomics, functional screens) with wet-bench experimental work
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Carilion (VTC). About the Lab: The lab integrates state-of-the-art neural recording technologies, complex cognitive tasks, and computational models to investigate the neural basis of flexible cognition. From