123 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" uni jobs at Oak Ridge National Laboratory
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strength of ORNL which is the U.S. Department of Energy’s largest Office of Science laboratory. ORNL is home to two user facilities in manufacturing – the Manufacturing Demonstration Facility (https
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, JAX etc.) Two or more years of experience in applying machine learning methods for instrument control, such as on a microscope, or on a nanomaterials synthesis platform resulting in publishable
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network, application, and/or security architecture and design. Familiarity with common protocols such as: DNS, DHCP, LDAP, SNMP, SMTP, HTTP, SSL. Special Requirement: This position requires the ability
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tools such as Puppet or Ansible. Experience in network, application, and/or security architecture and design. Familiarity with common protocols such as: DNS, DHCP, LDAP, SNMP, SMTP, HTTP, SSL. Special
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to interview, be sure to ask your Recruiter (Talent Acquisition Partner) for details. For more information about our benefits, working here, and living here, visit the “About” tab at https://jobs.ornl.gov
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the “About” tab at https://jobs.ornl.gov. This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired. We accept Word (.doc, .docx
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injection techniques, space charge simulation and theory, and control and mitigation of beam halo and other beam loss mechanisms, and machine learning efforts. Provide leadership to the group to support safe
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Analysis and Machine Learning Group. This group focuses on scientific computing with a strong emphasis on scientific machine learning and data analysis. We are specifically interested in applicants with
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Conduct of Research including being personally responsible for ensuring safe operations by raising safety concerns, using a questioning attitude, considering hazards for every task, and never stop learning
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of AI for science, including scientific reasoning, federated & collaborative learning, and reinforcement learning (RL) for self-improving models on leadership-class supercomputers. You’ll help design