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The Earth and Environmental Sciences Area at Lawrence Berkeley National Laboratory (LBNL) seeks a postdoctoral researcher to develop and curate unique and cutting-edge AI-ready data for the U.S
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that learn multiple-state adiabatic potential-energy surfaces, energies, gradients or forces, derivative nonadiabatic couplings, and state-transition behavior from electronic-structure data. Design reliable
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in the lab of Professor David Feinberg (MR physicist) at UC Berkeley, and collaborators at other sites. Specific duties include the following: Analyze fMRI data and integrate it with structural MRI and
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. We are looking for: PhD in chemical engineering, mechanical engineering, applied physics, materials science or closely related field. Hands-on experience with electrochemical devices such as PEM and
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collaboration with researchers from Argonne National Lab and Oak Ridge National Lab on a collaborative Department of Energy funded project “AlphaFold for Microelectronics”. The role will be to develop data
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to improve cryogenic calorimeter performance and optimize data analysis. Perform data analysis, support operations, and maintain electronics for the CUORE and CUPID R&D experiments. Support the development
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a curated catalysis database supporting AI-driven catalyst design. Release data, workflows, and benchmarks via the Materials Project and Genesis AmSC; publish in peer-reviewed journals and present
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with a focus on describing nucleon-nucleonshort-range correlations (SRCs). The successful candidate will bridge the gap between precision experimental data and modern theoretical frameworks, transforming
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for Advanced Mathematics for Energy Research Applications (CAMERA) has a new opening for a postdoctoral scholar to develop cutting-edge mathematics and algorithms to analyze complex data from Department
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: Ability to work with AI-agents. Requested Application Materials: Curriculum Vitae. Cover Letter. Statement of research experience and interests. Additional information: Application date: Applications will