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Until Filled No Desired Start Date 10/20/2025 Job Summary Candidate will work on DFT and atomistic simulation study of device materials and energy materials with machine learning potential development
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: You are open to feedback and act on it. You are enthusiastic about learning new experimental techniques that can be applied to solve real-world problems. You are highly motivated to pursue and establish
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materials; superconductivity; collective excitations (e.g., excitons, magnons, skyrmions); integer and fractional quantum (anomalous) Hall effects; machine learning approaches for quantum many-body problems
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assigned Knowledge, Skills & Abilities Demonstrate proactivity, independence, and creativity Motivation to learn and master new methods and techniques Excellent written and oral communication skills and the
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professional development opportunities, including a membership to Academic Impressions, LinkedIn Learning, and UT Dallas Bright Leaders Program. Visit https://hr.utdallas.edu/employees/benefits/ for more
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Options Paid time off Paid Holidays All UT Dallas employees have access to various professional development opportunities, including a membership to Academic Impressions, LinkedIn Learning, and UT Dallas
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resources, including memberships to Academic Impressions, LinkedIn Learning, and participation in the UT Dallas Bright Leaders Program. For full details, visit: https://hr.utdallas.edu/employees/benefits
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professional development opportunities, including a membership to Academic Impressions, LinkedIn Learning, and UT Dallas Bright Leaders Program. Visit https://hr.utdallas.edu/employees/benefits/ for more
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Impressions, LinkedIn Learning, and participation in the UT Dallas Bright Leaders Program. For full details, visit: https://hr.utdallas.edu/employees/benefits/ Special Instructions Summary Important Message 1
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access to a variety of professional development resources, including memberships to Academic Impressions, LinkedIn Learning, and participation in the UT Dallas Bright Leaders Program. For full details