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devices, with emphasis on lithium-ion, sodium-ion, and lead-acid battery systems. Modeling and analysis will leverage tools such as COMSOL, MATLAB, Excel, Python, and related scientific software. The role
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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather
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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
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, magneto-optic Kerr effect (MOKE) microscopy, and scanning NV microscopy. This position will also involve preparing suitable samples and devices using 2D material transfer systems and nanofabrication methods
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Laboratory’s Biosciences Division, allowing for seamless computational and experimental research integration Position Requirements A recent or soon to be completed PhD within the last 0-5 years Computational
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. The primary focus of this role will be in developing laboratory methods to improve recovery of microbial genomes from complex samples. Secondary focus of this role will be in maintaining cultures
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collaborative effort across XSD, the Materials Science Division (MSD), and the Chemical Sciences and Engineering Division (CSE). Key Responsibilities: Develop and enhance pump–probe sub-nanosecond TXS method
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in high-impact venues Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of High Energy Physics or Nuclear Physics, or a closely related discipline
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venues Position Requirements Required skills and qualifications: A PhD degree completed within the last 0-5 years (or soon to be completed) in numerical analysis, applied mathematics, computational science
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, superconducting nanowire particle detectors and pixelized MCP-PMTs. Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in experimental nuclear or particle physics or a related