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Field
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(PVES ) program at Jefferson Laboratory (JLab ), and Simulation studies & R&D for the future Electron Ion Collider (EIC ). For more information, please visit the PI’s website or the group’s nuclear
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machine learning algorithm to improve the modeled surface meltwater in the Goddard Earth Observing (GEOS) model. Advocating and adapting the model based on collaborator feedback is key to the success
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encompass: Catalysts Synthesis: Utilize your expertise in materials synthesis to develop novel catalysts guided by machine learning algorithms Catalyst Performance Evaluation: Utilize aqueous electrochemical
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inverter-based resources for performing real-time simulations in Opal-RT. Develop and prototype advanced control algorithms for grid forming and grid following inverters. Develop and demonstrate
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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through the Stanford Impact Labs Postdoctoral Fellowship Program (link is external) with Profs. Irene Lo, Itai Ashlagi, and the Stanford Impact Lab on Equitable Access to Education Postdoctoral Fellow
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computational models and systems using algorithms and analytics for materials and related physical sciences for a broad range of energy, transportation, and advanced manufacturing applications. Major Duties
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omics to advance biological and clinical discoveries and develop next-generation theragnostics. The postdoctoral fellows will mainly focus on (1) creating novel computational algorithms to analyze and
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algorithms for advanced and multi-modality imaging. Work on system designs, physics models, computation, benchtop experiments with small animals, and clinical translation. Additional areas of interest are in
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the complexities of the human regulome through advanced cell-free DNA profiling and developing cutting-edge computational algorithms and molecular profiling techniques. Our research focuses on early cancer detection