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component (ELM) and its peatland-specific configuration (ELM-Peatlands), with a focus on improving the representation of nutrient cycling dynamics and their coupling to hydrological and ecosystem processes
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advanced manufacturing processes. This position resides in the Deposition Science and Technology Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD) at Oak
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guided by AI/ML, remote sensing, process-based modeling, field observations and experiments, and advanced analytical techniques. Major Duties/Responsibilities: Independently and collaboratively lead field
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disturbance at scale. A cohort of postdoctoral researchers will be hired across multiple institutions to collaboratively support scientific advances guided by AI/ML, remote sensing, process-based modeling
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multiple institutions to collaboratively support scientific advances guided by AI/ML, remote sensing, process-based modeling, field observations and experiments, and advanced analytical techniques. Major
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fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD in Chemical Engineering, Materials Science & Engineering, Nuclear Engineering
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demonstrating advanced manufacturing technologies related to machining processes, machine tool performance, process monitoring, machine tool metrology, and/or manufacturing system integration. The successful
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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, and processing of materials under high temperature pyrolysis. The candidate will aid staff in conducting high quality research by developing, integrating, and deploying materials to be used
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and functionalized sorbents for the selective extraction and recovery of gallium (Ga), germanium (Ge), and other critical minerals from complex zinc-processing feedstocks. The successful candidate will