335 computer-security "https:" "https:" "https:" "https:" "U.S" "Brookhaven National Laboratory" positions at Oak Ridge National Laboratory
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structure, property, and function in support of the user program and theme science. Selection will be based on qualifications, relevant experience, skills, and education. Functional Hybrid Nanomaterials
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. The goal of this work is to investigate the dynamics of beams with intense space charge and benchmark simulation models against experimental results. As a U.S. Department of Energy (DOE) Office of Science
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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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multiple types of sensing modalities, where this expertise is applied to solve critical national problems in energy and security. Demonstrated knowledge of emerging AI and machine learning techniques as
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/infrastructure: virtualization, networks, security, system integration. Establish system architecture and infrastructure design: servers, network, storage, compute, security (including access controls, encryption
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with codes and regulations, and observe all safety rules. Preferred Qualifications: Completion of an apprenticeship program and/or formal training programs as well as industrial experience is preferred
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position. WSAP positions require passing a pre-placement drug test and participation in an ongoing random drug testing program. Security, Credentialing, and Eligibility Requirements: For employment at Oak
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with environmental, safety, health, industrial hygiene, and quality program requirements. Be able to wear PPE, such as but not limited to respiratory protection and anti-contamination clothing. Deliver
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of materials, layout techniques and shop safety. General computer. Ability to work and coordinate effectively with others and maintain positive working. Ability to give full attention to what other people
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a particular emphasis on error-corrected methods for future fault-tolerant quantum computing. The algorithms will be designed to address key models of quantum materials, such as the Hubbard model