273 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" positions at University of Texas at Dallas
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to various professional development opportunities, including a membership to Academic Impressions, LinkedIn Learning, and UT Dallas Bright Leaders Program. Visit https://hr.utdallas.edu/employees/benefits
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libraries. Knowledge of HPC job execution environments like SLURM, PBS, or similar. Knowledge of launcher and array jobs. Understanding of computer architecture elements that affect code performance
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Impressions, LinkedIn Learning, and UT Dallas Bright Leaders Program. Visit https://hr.utdallas.edu/employees/benefits/ for more information. If you are looking for a rewarding career opportunity with great
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Posting Details Posting Details Posting Number F01001P Position Title Part-time Lecturer - Electrical and Computer Engineering Functional Title Part-time Lecturer - Electrical and Computer
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membrane biophysics. https://labs.utdallas.edu/shukla/ Minimum Education and Experience Ph.D in a related field. Preferred Education and Experience To ensure a strong fit for the role, candidates with
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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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visiting university and government officials to promote global education and commerce. The selected candidate will be expected to teach undergraduate and graduate courses, with particular emphasis on Study
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the UT Dallas Initiative for Civic Leadership. The ideal candidate should be experienced in university instruction at the graduate and undergraduate levels and be able to teach a wide range of political
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accounting. Candidates will be required to conduct high-quality research and publish their research in top journals in the accounting area and to develop and teach accounting courses at undergraduate and
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methodologies for sustainable and smart manufacturing, and incorporation of artificial intelligence, machine learning and/or digital twins in materials science research. Outstanding candidates in advanced micro