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expected to have experience in hydrologic/hydraulic modeling and in one or more of the following topics: in situ sensor installation and flood monitoring, GIS & geospatial big data, AI/ML and data science
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a related field Experience with radiation transport codes (e.g., FLUKA, Geant4, MCNP etc.) Excellent programming and data analysis skills (e.g., Python, C++, or similar) Solid understanding
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environment using models and data assimilation. We study the fundamental processes in the near-Earth environment and focus on understanding fundamental processes responsible for the evolution of space radiation
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protostellar evolution models to radiative transfer grids. The goal is to synthesize these protostar models into protocluster models and compare them to JWST and ALMA data. The applicant must have a Ph.D. in
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required Working knowledge of all aspects of planning and deploying an AI project, including initial problem specification, data gathering and analysis, model creation, and implementation Strong
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Associates to join our team. In this role, you will be responsible for the installation and commissioning of the newly upgraded CMS detector, as well as the analysis of CMS data. If you are driven by curiosity
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analysis Large language models or machine learning/predictive modeling for longitudinal data analysis Strong computer programming skills Strong mathematical or statistical skills Ability to work as a part of
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, including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and
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activities such as working with large public datasets, designing and implementing relevant experiments writing manuscripts, presenting research, and mentoring undergraduate and graduate researchers in
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space-based systems, including large satellite constellations. A recent PhD in physics, engineering, computer science, or other relevant fields and strong interest in technical and policy research