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advanced manufacturing technologies related to machining processes, machine tool performance, process monitoring, machine tool metrology, and/or manufacturing system integration. The successful candidate
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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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coordinate cross-functional teams of researchers, platform engineers, and application developers to move AI capabilities from prototype to production. This often includes mentoring teams on best practices
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changing needs For additional information, contact Dr Adam Guss (https://www.ornl.gov/staff-profile/adam-m-guss ; email address [email protected] ) or Dr Carrie Eckert (https://www.ornl.gov/staff-profile
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Engineer (ME) will facilitate the process to determine internal or external fabrication. This process includes evaluation of design, submitting RFQ’s/awarding of projects, maintaining schedules/records
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treat one another, work together, and measure success. Basic Qualifications: BS degree or higher in Software Engineering, Electrical Engineering, Computer Engineering, or closely related engineering
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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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the Machine Design Engineering Group Leader to deliver task assignments and design outputs while following established design processes. This position works closely with other ESED subject matter experts
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the Machine Design Engineering Group Leader to deliver task assignments and design outputs while following established design processes. This position works closely with other ESED subject matter experts
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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