1,327 computer-science-programming-languages-"St"-"St" positions at University of Texas at Austin
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energy-related research challenges in the Greater Permian Basin region. This position will support the State of Texas Advanced Resource Recovery (STARR) program at the Bureau of Economic Geology (BEG
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Retirement System of Texas, a defined benefit retirement plan, with 8.25% employer matching funds Additional Voluntary Retirement Programs: Tax Sheltered Annuity 403(b) and a Deferred Compensation program 457
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the world. The University of Texas at Austin, founded in 1883, ranks among the 40 best universities in the world with top national programs across 19 colleges and schools. By creating educational
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organizations. Proficiency in programming languages and frameworks including Python, Django Rest Framework, FastAPI, JavaScript, TypeScript, React, Next, and Node.js. Strong understanding of AI/ML frameworks (e.g
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8.25% employer matching funds Additional Voluntary Retirement Programs: Tax Sheltered Annuity 403(b) and a Deferred Compensation program 457(b) Flexible spending account options for medical and childcare
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. Perform cost analysis and estimates. Other related functions as assigned. Required Qualifications A bachelor’s degree in Computer Science, Software Engineering, or equivalent or 4 years of relevant
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Qualifications One year of experience in a testing services role or working with students in a higher education program. Salary Range $21.00 hourly Working Conditions May work around standard office conditions
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and the Sports Administration department at the University of Texas. Responsibilities Roster Management: Facilitate the timely and effective management of sport program rosters at the direction
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) and a Deferred Compensation program 457(b) Flexible spending account options for medical and childcare expenses Robust free training access through LinkedIn Learning plus professional conference
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across the college (e.g., Program Offices) to share data and insights and foster a culture of data-informed decision-making. Identify opportunities for data-driven innovation in Career Management, such as