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user groups to incorporate scattering datasets into multimodal AI frameworks combining experimental measurements and simulations. Contribute to the development of automated data processing and analysis
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) simulations and reduced order modeling of turbulent and reacting flows relevant to advanced propulsion and power generation systems, such as gas turbines and detonation engines. The successful candidate’s
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, co-simulation, or hardware-relevant environments. Primary Responsibilities: Develop machine learning and AI methods for control, optimization, and cyber-resilient operation of distribution systems, DER
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) Perform low-noise cryogenic measurements of device performance, including timing jitter, dark count rate, detection efficiency, and resonator quality factors Iterate rapidly on fabrication processes and
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, safety, respect, integrity, and teamwork Preferred Skills Hands-on experience with GEANT4-based simulations Experience with detector characterization and validation Familiarity with HEP/NP data processing
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architectures and device technologies Developing and applying simulation and modeling tools for detector performance, characterization, and validation Providing technical feedback to guide intelligent on-detector
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The Computational Science Division (CPS) at Argonne National Laboratory (near Chicago, USA) is seeking a postdoctoral researcher to enable exascale atomistic simulations of ferroelectric devices
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
mathematics, or a related field Candidates should have expertise in two or more of the following areas: Uncertainty quantification, numerical solutions of differential equations, and stochastic processes
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to quantify energy consumption, performance and cost benefits. In this role, a successful candidate will perform vehicle modelling and simulation of advanced powertrains to quantify the impacts of new component
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at the University of Chicago, automating screening protocols in partnership with Argonne National Laboratory Drive research at the intersection of automation, robotics, generative AI, and computational simulations