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(HPC), or large-scale data analysis. Experience in applying AI/ML techniques to hydrological and Earth sciences. Proficiency in scientific programming languages such as Python, Julia, R, Fortran, or C/C
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bioenergy. The research supports missions for multiple program offices within the U.S. Department of Energy (DOE), including Office of Science, Office of Nuclear Energy, Office of Fusion, Hydrocarbon and
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performance for datacenter applications, especially Large Language Models (LLMs) Drive the discovery of opportunities for innovation in GPU, system, and data-center architecture by analyzing the latest data
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courses. Programs included are Electrical Safety, Hoisting & Rigging, Fall Protection, HAZWOPER, Confined Space, and various other Environment, Safety and Health-related topics. This position resides in
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structure, property, and function in support of the user program and theme science. Selection will be based on qualifications, relevant experience, skills, and education. Functional Hybrid Nanomaterials
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must possess the ability to function in a fast-paced business environment requiring a high degree of accuracy. Excellent attention to detail and well-developed written and oral communication skills
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++ or other scientific programming languages is also often preferred. Excellent analytical and problem-solving skills are critical for diagnosing and resolving complex technical issues. Strong verbal and
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, XGBoost, LSTM, clustering techniques, etc.) to solve hydrology and water resources research problems. Scripting and programming skills, with strong knowledge of at least one of the following languages
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program requirements. Maintain strong commitment to the implementation and perpetuation of values and ethics. Align behaviors, priorities, and interactions with our core values of Impact, Integrity
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skills. Preferred Qualifications: Excellent written and oral communication skills. Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across