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subject to continuing based on the availability of funding. The work will focus on the production of large polarimetric maps from the SOFIA data. The position is planned for two years, with a possible
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Research Associate. The Goodwill Computer Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning
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, with a particular emphasis on Urban Resilience to Climate Risks. Current research themes include: • Adaptation of People: Leveraging big data and computational methods to analyze adaptation behaviors and
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agents for X-ray spectroscopy by integrating large language models (LLMs) with physics-aware spectroscopy workflows. The researcher will work closely with a multidisciplinary team of X-ray physicists and
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Science, Computer Science, or a related field; familiarity with large-scale data management, curation, and FAIR data principles; experience with plasma physics, MHD stability, or fusion energy research
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Ph.D. (or equivalent) in Astronomy, Astrophysics, Physics, Planetary Science, or a closely related field by the start date. Demonstrated experience in one or more of: large-scale data analysis, time
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proficient in working with large data-sets (observational or numerical), machine learning, and running/analyzing numerical simulations. The initial appointment will be for two years at Rutgers University
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disease, including AI-powered tools and new statistical techniques that leverage large datasets, heavy computational capabilities, and/or a robust understanding of biological systems to provide unique
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Job Description Job Responsibilities: -Design and implement AI/ML models to analyze large-scale agricultural datasets (e.g., field trials, satellite imagery, IoT sensor data). -Develop pipelines
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sciences. The fellow will work alongside Dr. Leslie McClure, Dean of CPHSJ, and contribute to the development and application of advanced statistical methodologies to analyze large-scale health-related