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University of New Mexico’s Center for Advanced Research Computing (CARC), within the Department of Computer Science, seeks a full-time Postdoctoral Researcher to lead development of an open-source
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generation of atomic structures and training of machine learning interatomic potentials (MLIPs) in a way that maximizes the capability of high-performance computing (HPC) platforms available in the Oak
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systems, targeting high performance & energy-efficiency, robustness, and trustworthiness. A key focus will be on IP generation, patenting, high-quality publications in top-tier ML/AI, Robotics, and Systems
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systems, targeting high performance & energy-efficiency, robustness, and trustworthiness. A key focus will be on IP generation, patenting, high-quality publications in top-tier ML/AI, Robotics, and Systems
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. conduct theoretical and experimental performance analyses of the proposed algorithms. publish research results in high-quality venues (conferences and journals) and present them in national and
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systems, targeting high performance & energy-efficiency, robustness, and trustworthiness. A key focus will be on IP generation, patenting, high-quality publications in top-tier ML/AI, Robotics, and Systems
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sensing data, including data processing and analysis using tools such as GDAL, Google Earth Engine, or similar platforms, and working in cloud or high-performance computing (HPC) environments
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. Experience running work on high-performance or cloud computing resources. A record of contributing to open-source scientific software. Additional Information: Location: Dreese Laboratories (0279) Position
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, providing access to national data networks, high-performance computing clusters, and clinical interdisciplinary collaborations across UT Austin. The applicants will join a collaborative research
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., near-miss detection, predictive crash risk, multimodal exposure estimation). · Design, implement, and validate AI pipelines (computer vision, tracking, spatio-temporal modeling, edge learning