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Field
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multidisciplinary team of scientists and High Performance Computing (HPC) engineers. In the AL/ML group, we work at the forefront of HPC to push scientific boundaries, carrying out research and development in state
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microbiome data and/or analyzing sequencing data in a high-performance computing environment. Experience in BSL2 laboratory and familiarity with ELISA techniques. Demonstrated fieldwork experience in community
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 21 hours ago
equivalent doctorate (e.g., Sc.D., M.D.) Departmental Preferred Experience, Skills, Training/Education: Ph.D. in Political Science, Economics, Public Policy, Geography, or a closely related Computational or
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functions, predictive models or quantum chemistry Machine learning or AI frameworks applied to molecular discovery. Familiarity with cloud or high-performance computing environments. Experience collaborating
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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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, sequencing library preparation). Experience with analyzing microbiome data and/or analyzing sequencing data in a high-performance computing environment. Experience in BSL2 laboratory and familiarity with
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for state-of-the-art high performance computing architectures. Study the dynamics and properties of lattice models of nonequilibrium quantum materials using innovative computational techniques. Collaborate
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to 1) digital twin technologies; 2) complex multiscale simulations and modeling; 3) large-scale hybrid machine learning and high-performance computing workflows; 4) tools and methods to allow productive
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Mississippi. Apply computer vision and machine learning approaches to integrate ground-based imagery, remote sensing data, and lidar data for high-resolution flood detection and mapping. Develop and calibrate
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, molecular biology, and in vivo models. Analyze and interpret data, integrating experimental and computational findings. Utilize bioinformatics tools and techniques to analyze high-throughput sequencing data