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be overseen by Professor Yimei Zhu and emphasizes strong collaborations within the DOE-EFRC — “Quantum Materials for Energy Efficient for Neuromorphic Computing.” The position is ideal for candidates
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seminars and colloquia Participate in conferences and workshops, regular group meetings, and assist with notetaking Required Knowledge, Skills, and Abilities: PhD degree in meteorology, atmospheric sciences
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experiments at NSLS-II. The selected candidate will work with a team of scientists from NSLS-II, CFN (Centers for Functional Nanomaterials), CSI (Computational Science Initiative), and IO (Instrumentation
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processes emerging from the unique data in research areas such as quantum information science. • You will collaborate with scientific staff with diverse backgrounds, including data analytics, electron
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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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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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computational resources for data analysis. This position offers a dynamic, collaborative environment, engaging with experts across plant biology, microbiology, structural biology, and computational sciences and
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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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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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, and readout electronics. POSITION DESCRIPTION Experimental and practical Quantum Information Science and Technology (QIST) is a key area of R&D for BNL. The successful candidate will join a fast-growing