28 parallel-computing-numerical-methods-"DTU" Fellowship research jobs at University of Texas at Austin
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-grade software for large-scale numerical experiments. PhD must have been obtained within 3 years from date of hire. Preferred Qualifications Ph.D. degree from a computation-intensive program, such as
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Job Posting Title: Postdoctoral Fellow, PhARM Program, College of Pharmacy ---- Hiring Department: College of Pharmacy ---- Position Open To: All Applicants ---- Weekly Scheduled Hours: 40 ---- FLSA
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research projects exploring how social contexts and experiences of marginalization influence development, family processes, and health. Ideal candidates will have knowledge of advanced quantitative methods
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the Nuclear and Radiation Engineering Program to advance research in nuclear reactor multiphysics, digital twin methods, and uncertainty quantification for high-performance computing platforms using VERA, MOOSE
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Postdoctoral Fellow - Materials Chemistry, Texas Materials Institute, Cockrell School of Engineering
or parallel reactors Collaborate with computational scientists to integrate machine-learning models for closed-loop materials discovery Collaborate with companion postdocs on functional materials
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communication skills Strong logistical coordination skills Training in advanced statistical techniques and computational methods Experience managing and analyzing large, administrative datasets The ability to balance
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Postdoctoral Research Fellow to start in Fall 2026 to work with Associate Professor Peter Bergman. The Fellow will contribute to a research program focused on AI applications for economic mobility, such as
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challenges in developing AI systems and human-AI collaboration methods to. reliably improve outcomes in health care and other high-impact contexts, benefiting people, organizations, and society at large. We
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meetings and short courses. Publish findings in BEG Reports of Investigation, peer-reviewed international journals, and informal reports. Utilize high-performance computing techniques in simulation studies
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Qualifications Strong written and oral communication skills Strong logistical coordination skills Training in advanced statistical techniques and computational methods Experience managing and analyzing large