60 materials-science research jobs at Lawrence Berkeley National Laboratory in United-States
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Lawrence Berkeley National Lab’s (LBNL ) has an opening for a Material Sciences Postdoctoral Fellow to join the team. In this exciting role, you will be part of the Non-Equilibrium Magnetic
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process design, simulation, scaling science, scenario modeling, and techno economic analysis. The emphasis will be on hydrogen storage materials and hydrogen end uses, gas separation technologies such as
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engineering, mechanical engineering, materials science or related field. Demonstrated experience in structure-property characterization of solid-polymer electrolytes and interfaces, ionomer membranes and thin
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Science Acceleration Program (NESAP). NESAP postdocs collaborate with scientific teams to enable the solution of deep, meaningful problems across all program areas funded by the Department of Energy Office
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The National Energy Research Scientific Computing Center (NERSC) at Berkeley Lab seeks a highly motivated postdoctoral fellow to join the Data Science Engagement team as part of NERSC’s Exascale
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Exascale Science Acceleration Program (NESAP). NESAP postdocs collaborate with scientific teams to enable the solution of deep, meaningful problems across all program areas funded by the Department of Energy
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Lawrence Berkeley National Lab’s (LBNL ) Materials Sciences Division has an opening for a Postdoctoral Fellow to join the team. Berkeley Lab is leading a new Energy Frontier Research Center—Center
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Lawrence Berkeley National Lab’s (LBNL ) Building Technology & Urban System (BTUS) Division has an opening for an Energy/Environmental Technology Researcher to join the team. The EETR1 will be
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Lawrence Berkeley National Lab’s (LBNL ) Accelerator Technology & Applied Physics (ATAP ) Division has an opening for a Research Assistant to join the Fusion Science & Ion Beam Technology’s (FSIBT
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Required: Ph.D., in mechanical engineering, physics, materials science and engineering, within the last 3 years. Specialization in nano-scale thermal transport preferred. Knowledge and experience in modeling