8 big-data-and-machine-learning-phd Postdoctoral positions at Lawrence Berkeley National Laboratory
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experimental data. Apply modern methods of machine learning towards predictive data analysis. Collaborate with other research teams and scientists. Publish original research in peer-reviewed journals and
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the validation of quantum computers operating in the classical-hardness regime. You will design and execute state-of-the-art experiments on superconducting quantum processors, lead large-scale benchmarking across
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data interpretation and analysis. Perform in-situ/operando spectroscopic characterization such as surface-enhanced in-situ Raman and ambient-pressure XPS (AP-XPS). Fabricate catalyst ink, electrodes and
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quantum computer control systems. Assist in developing and testing PCB boards. What is Required: Ph.D. degree in physics, applied physics, electrical engineering, or a related field within the last 3 years
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conferences. Engage in community knowledge-sharing (e.g. tutorials for the NERSC user base). What is Required: PhD awarded within the last five years in Physics, Computational Chemistry, Computational Science
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REAL ID or other acceptable form of identification is required to access Berkeley Lab sites (for more information click here ). Want to learn more about working at Berkeley Lab? Please visit
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and contact information for three references. PDFs of 2 top publications (in prep is OK). Additional information: Application date: Priority consideration will be given to candidates who apply by 12/31
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other acceptable form of identification is required to access Berkeley Lab sites (for more information click here ). Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov Equal