44 postdoc-in-thermal-network-of-the-physical-building research jobs at University of Texas at Austin
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of Texas through August 2027, but the applicant is expected to build a sustainable research program that can include funding from the commercial nuclear and thermal storage industries, US Department of
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| Human Resources and UT Austin Employee Experience | Human Resources Must be authorized to work in the United States on a full-time basis for any employer without sponsorship. Purpose The Postdoc employed
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, Synopsys/Ansys, Siemens). Willingness to work on cross-stack optimizations and learn new skills. Preferred Qualifications Experience with multi-physics simulations for thermal, mechanical, and reliability
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. Collaborate effectively with staff, postdocs, and students in the research group and collaborators of the group. Present results to the scientific community and broader public through conference presentations
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multidisciplinary team of researchers and students and will be responsible for executing laboratory and field-based research designed by the team to address relevant research questions. The Postdoc is expected
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Postdoctoral Researcher will have access to mentorship, networking, and professional development resources offered through the Jackson School for Geosciences and the University of Texas Office of Postdoctoral
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convolutional neural networks (CNNs), generative AI methods such as diffusion models, and interpretability techniques commonly applied in hydrology including SHAP or LIME for explaining outputs of forecasting
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application process. Then, any additional Required Materials will be uploaded in the My Experience section; you can multi-select the additional files or click the Upload button for each file. Before submitting
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continuity of care Participates in the anesthesia time-out process if performed in the pre-op area prior to administration of pre-operative blocks or prior to the induction of anesthesia. Responsible
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) surface water modeling environments (e.g., Texas water availability models, HEC-RAS, etc.), (h) rainfall runoff process modeling, and (i) drought metrics. Familiarity with Texas surface water resources and