686 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" uni jobs at University of Texas at Austin
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an impressive benefits package. For more details on benefits, please see: https://hr.utexas.edu/prospective/benefits and https://hr.utexas.edu/current/services/my-total-rewards For more information about the
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. Further information about the Department is available on our website: http://www.utexas.edu/cola/depts/classics/ . Qualifications Applicants must hold a Ph.D. in Classical Studies or a closely related field
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an internationally recognized research program at the University of Texas, mentor graduate students, and teach at the undergraduate and graduate levels. The predominant mode of instruction and research is in-person
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. Successful applicants will be expected to establish an internationally recognized research program at the University of Texas, mentor graduate students, and teach at the graduate and undergraduate levels
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for medical and childcare expenses Robust free training access through LinkedIn Learning plus professional conference opportunities Tuition assistance Expansive employee discount program including athletic
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offers an impressive benefits package. For more details on benefits, please see: https://hr.utexas.edu/prospective/benefits and https://hr.utexas.edu/current/services/my-total-rewards . For more
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and graduate learning environments that address the needs of students from a variety of backgrounds, with differing learning styles and abilities. Further, the successful applicant will be expected
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expected to create undergraduate and graduate learning environments that address the needs of students from a variety of backgrounds with differing learning styles and abilities. Further, the successful
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recognized record of research and scholarship, and possess the qualities necessary for academic leadership. The successful candidate will be expected to create undergraduate and graduate learning environments
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model or machine-learning-enabled assets at a company or University). Basic understanding of early-stage technology development. Knowledge of basic principles of intellectual property and licensing