50 algorithm-development-"University-of-Surrey" Postdoctoral positions at Argonne in United States
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We are seeking a highly motivated and flexible postdoctoral researcher to join the Applied Materials Division (AMD) at Argonne National Laboratory to develop advanced methods for in situ and
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readout and controls (e.g., SQUID-based time- or microwave-multiplexed systems) with beamline data acquisition and control (EPICS/Bluesky). Develop and maintain data acquisition, calibration, and analysis
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contribute to research and model development to enhance the resilience of domestic and global supply chains for clean energy technologies. Lead technical and policy analysis to inform decision-makers
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insights and develop reduced order models (ROMs) for boundary layer flows and turbulent combustion. Integrate ROMs with CFD solvers and demonstrate predictive accuracy compared to traditional modeling
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specifically on developing machine learning-based surrogates and emulators for the dynamics of power grids. This role involves creating advanced probabilistic models that capture the complex behaviors
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laboratory partners, and contribute to the development of separation technologies for energy, water, and critical resources. Key Responsibilities: Develop and apply in-situ methods (e.g., optical coherence
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Separations Postdoctoral Research Associate will develop capacitive deionization systems for the selective recovery of critical materials and also investigate electrode aging, degradation, and durability
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experimental studies that will develop novel functionalization strategies for tethering redox-active molecules to carbon surfaces for selective, electrochemical capture of critical minerals. This position will
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Argonne National Laboratory is seeking a highly skilled Postdoctoral Researcher to work in the Separations and Bioprocessing Group on developing, designing and characterizing new polymers and
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candidate will work on cutting-edge research integrating genome-scale language models (GenSLMs) with deep mutational scanning data, and experimental virology to predict viral evolution and identify emerging