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respectful workplace – in how we treat one another, work together, and measure success. Required Qualifications: PhD in Nuclear engineering, computer science, applied mathematics, or a related field completed
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nuclear engineers and radiochemists to organic chemists and cell biologists, IARG pushes the boundaries of technology in the production, isolation, and characterization of radionuclides. Their work not only
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committees. Distinguished record of achievement and recognition. Preferred Qualifications: Advanced technical degree (MS or PhD) in a science or engineering field with at least 8 years of experience managing
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opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: Candidates must have a MS degree or PhD in Nuclear engineering, computer
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supporting the management and oversight of the ORNL classification program and the classification of scientific, technical, and other information as well as provide Unclassified Controlled Nuclear Information
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contribute and succeed. Basic Qualifications PhD in data science, mathematics, physics, or engineering with a minimum of 8 years of relevant experience, or MS in these areas with a minimum of 12 years
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measure success. Basic Qualifications: PhD in nuclear physics or related field. 5 years of experience in a relevant research field beyond PhD. Extensive knowledge in low-energy nuclear physics. Ability
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Engineering, Nuclear Engineering (focus on Materials), or a closely related field. A minimum of 6 years of research experience post PhD in relevant field. Experience in at least one leadership position within a
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Qualifications: PhD in radiation biology, health physics, nuclear engineering, computational biology, or related areas, with experience in performing radiation dosimetry research Experience in occupational and
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. Basic Qualifications: PhD in electrical/computer engineering, computer science, or a related discipline A minimum of 8 years of relevant experience in image/signal processing and machine learning