26 materials-science Postdoctoral research jobs at Lawrence Berkeley National Laboratory in United-State
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of scientists and engineers making significant impacts in stride in the fields of materials science and energy. Join our dynamic team at the The Materials Sciences Division , where we are pioneering the future
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Lawrence Berkeley National Lab (LBNL ) is an inclusive and supportive community of scientists and engineers making significant impacts in stride in the fields of materials science and energy. Join
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Center and the NERSC scientific computing center, as well as Berkeley Lab's outstanding programs in materials and chemical sciences, among others – offers a prime environment for collaborative science. The
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areas, focusing on integrating and analyzing complex data from simulations and experiments. You will work in a multidisciplinary team, collaborating with scientists from biosciences, physical sciences
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for earth system and climate science. What You Will Do: Develop and apply reactive transport models to quantify weathering rates of silicate amendments at field scale. Integrate diverse data
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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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Accelerator Technology & Applied Physics (ATAP) Division to primarily conduct accelerator magnet superconductor and associated materials R&D and characterization. In this role, work will be performed within
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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