358 assistant-professor-computer-science-data positions at Oak Ridge National Laboratory
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-placement drug test and participation in an ongoing random drug testing program. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy
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a pre-placement drug test and participation in an ongoing random drug testing program. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80
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) Biological and Environmental Research (BER) program. This position resides in the BER Information Systems Group in the Biosciences Division, Biological and Environmental Systems Science Directorate, at Oak
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will be part of a dynamic team within the National Security Sciences Directorate, working alongside experts in data science, statistics, nuclear engineering, and scientific computing to support high
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opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A BS degree in computer science, computer engineering, physics science or
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or other large research organizations. Ability to interpret engineering drawings and technical design documentation. Demonstrated ability to manage multiple research activities and adapt to evolving program
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adversaries. The directorate houses S&T leadership in cybersecurity and cyber-physical resiliency, data analytics, geospatial science and technology, nuclear nonproliferation, and high-performance computing
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, and compliance requirements. Strong aptitude for computer systems, electronic tools, and digital workflows. Ability to learn and adapt to new technologies, including AI-enabled tools used to support
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Requisition Id 15751 Overview: The Advanced Computing in Health Sciences (ACH) section at the Oak Ridge National Laboratory is seeking qualified applicants for a Machine Learning Engineer position
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Qualifications: An MS in computer science, mathematics, or a related field completed within the last 5 years. A BS degree and at least 2 years of relevant research experience will also be considered. Familiarity