54 postdoctoral-position-in-material-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. The Center for Non-Perturbative Studies of Functional Materials under Non
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chemistry methodologies. Notes: This is a full-time 2 year, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing
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3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree. This position is represented by a union for collective bargaining purposes
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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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postdoctoral experience. The monthly salary range for this position is $5,643-$6,766 and is expected to start at $5,643-$6,766 or above. Postdoctoral positions are paid on a step schedule per union contract and
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Berkeley Lab’s (LBNL ) Molecular Biophysics and Integrated Bioimaging Division (MBIB ) has an opening for a Postdoctoral Fellow to use structural biology on global health problems and
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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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operational needs. You must have less than 3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree. The monthly salary range for this position is
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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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an opening for a Computational Biology Postdoctoral Fellow in Health Sciences. In this exciting role, you will work on computational analysis, data integration and machine learning among other methods directed