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classification, and dynamic process tracking using deep-learning and physics-informed models. Integrate TEM operations with robotic sample handling, including the design, testing, and deployment of a robot-arm
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diverse scientific instruments Build and refine digital twins for synthesis and characterization workflows, using physics-based simulations and/or surrogate ML models Collaborate closely with
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Postdoctoral Fellow - Materials Chemistry, Texas Materials Institute, Cockrell School of Engineering
characterization (XRD, SEM/TEM, Raman, spectroscopy, electrochemical analysis, etc.) Performs other related duties as assigned Required Qualifications Ph.D. in Materials Science, Engineering, Physics, Chemistry, or
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professional interests. Along with Archer Center campus partners from across the UT System institutions, serve as a strategic partner to the Archer Center by periodically reviewing the fellow selection process
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technologies Experience with project management and collaborating in academic/industrial research environments Proficiency in hands-on lab work, including ink formulation, device fabrication, and physical
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. The Ransom Center is an internationally renowned humanities research center at The University of Texas at Austin. Our extensive collections provide unique insight into the creative process of some of our
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in this position will conduct/lead applied as well as fundamental research in physics-informed Artificial Intelligence (AI) and Machine Learning (ML) methodologies enabling digital twin functionalities
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includes a suite of initiatives that include the development of digital twins for physical systems at many institutions, development of high-fidelity, multiphysics software that models advanced reactors
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to investigate ocean-estuarine dynamics in the Gulf Coast. Integrate empirical data (physical and chemical observations and ecological data covering from microbes to fishes) to parameterize and validate models
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process. Purpose The Meyers Lab and epiENGAGE at The University of Texas at Austin are immediately seeking outstanding postdoctoral scholars to contribute to modeling the spread, surveillance, forecasting