21 computational-solid-mechanics Postdoctoral positions at Brookhaven Lab in United States
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transformations, quantum information science, microelectronics and energy storage. The research will involve the use of pulse radiolysis at the Chemistry Division’s 9 MeV Laser Electron Accelerator Facility (LEAF
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support. Preferred Knowledge, Skills, and Abilities: Ability to program and debug python code, particularly Jupyter notebooks. Experience in working on collaborative software projects. Environmental, Health
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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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work closely with CFN Electron Microscopy group members and computer scientists at Brookhaven. You will be professionally mentored by Dr. Judith Yang and Dr. Sooyeon Hwang and receive guidance from Prof
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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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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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Apply Now Job ID JR101446Date posted 09/26/2024 The AI/ML Department of Computational Science Initiative (CSI) at Brookhaven National Laboratory (BNL) invites exceptional candidates to apply for a
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for highly motivated postdoctoral researchers to conduct advanced electron microscopy studies on quantum materials for neuromorphic computing. The primary objective of this research is to explore quantum
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at the Computational Science Initiative (CSI), within the Brookhaven National Laboratory. The selected candidate will collaborate on solving inverse problem, relevant for interference lithography process, by deploying
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these applications to inform new foundational ML and NLP innovations. The position provides unique access to world-class computing resources, such as the BNL Institutional Cluster and DOE leadership computing