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majoring in Computer Science or a related field: (e.g., engineering, applied mathematics, statistics, physics). The ideal candidate must be currently enrolled in a Bachelor Degree program and have maintained
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class science to occur in a safe and secure environment. The Police Group within LP, protects classified matter, special nuclear materials, hazardous materials, and property against theft, diversion
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applies platforms for state-of-the-art techniques for Accelerated Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a
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materials for the next generation of microelectronics and quantum information science and technology. Position Description: We are looking for a Postdoctoral Research Associatefor a 1-year term , to grow high
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programming skills and in-depth computer science knowledge. Preferred Knowledge, Skills, and Abilities: Practical experience developing novel AI/ML algorithms and models. Knowledge about foundation models and
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the virtual Student Teaching Assistant will attend each lecture and lead their respective workshops to aid the students in successfully completing the program. Essential Duties and Responsibilities: Directly
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, cryogenic components, and water/air cooled systems. Join BNL at the beginning of this ground-breaking scientific and engineering project and become part of the team building this scientific discovery machine
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of tools and equipment in the shop areas and participates in Safety inspections and audits. Monitors employee training and attendance records. Monitor cross connection program for regulatory compliance
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the equivalent tools associated with the EIC Project scope. Required Knowledge, Skills, and Abilities: BA/BS Degree (or equivalent experience), preferably in Computer Science or a related discipline At least ten
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candidates should have a major in electrical engineering, computer science, or applied mathematics. A background in electric power systems modeling and simulation and data analytics and machine learning