112 computer-programmer-"Multiple"-"U"-"O.P"-"Duke-University" "U.S" positions at Brookhaven Lab
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sciences, and nanoscience. To support this program, the NSLS-II must design, fabricate, assemble, test, install, and operate unique research equipment to generate, transport, transfer, accelerate and focus
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, policies, and procedures. Environmental, Health & Safety Requirements: The incumbent will occasionally work protracted or irregular hours. Computer / keyboard work is an essential duty. Compensation
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Microsoft Office suite. Familiarity with Power Business Intelligence. Familiarity with Workday. Environmental, Health & Safety Requirements: The ability to work at a computer/keyboard for extended periods is
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studies and computer simulations Collaborate with the BMAD development team at Cornell University by implementing new features into the code Participate in the EIC design effort in a more general sense
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hands-on with mechanical equipment, and collaborating with a team to develop and build unique equipment. Demonstrated ability with 3D Computer Aided Design modeling software. Ability to perform mechanical
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Apply Now Job ID JR101895Date posted 07/17/2025 Brookhaven National Laboratory (BNL) is the building site for the Electron-Ion Collider (EIC), a one-of-a-kind nuclear physics research facility. The EIC will be a discovery machine for unlocking the secrets of the “glue” that binds the building...
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Apply Now Job ID JR101405Date posted 09/12/2024 The Machine Learning Group of the Computational Science Initiative (CSI) at Brookhaven National Laboratory (BNL) invites exceptional candidates
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(ITD) mission is to deliver safe, efficient operations that ensure the delivery of the Lab's research mission by: Developing and deploying state-of-the-art information and computing systems in support of
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: Plan, carry out, and publish independent and impactful science research utilizing LEAF’s ultrafast capabilities (~ 10 ps resolution). Present scientific results at domestic and international conferences
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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