26 programming-"the"-"DAAD"-"IMPRS-ML"-"UCL"-"U"-"FEMTO-ST"-"FCiências" Fellowship positions at University of Texas at Austin
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program of the Department of Mathematics is consistently ranked among the best by US News, with several research areas in the top ten. Our core faculty includes around 50 tenured and tenure-track members
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symposium on campus that involves collaboration with other programs and units on campus, such as the Humanities, Health & Medicine Program, the Dell Medical School, and the College of Natural Sciences Present
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the last three years. Solid experience with AI/machine learning methodologies, particularly those applicable to network optimization. Proven ability in programming and familiarity with network simulation
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pressing challenges of the 21st century through world class research, unsurpassed student education, and dedicated service to the community. The Digital Molten Salt Reactor Initiative (D’MSRI) is a program
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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(b) Flexible spending
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, within the last 3 years, in oceanography, ecology, computer science or related discipline Demonstrated proficiency in a programming language, along with strong computational and quantitative skills in
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the last three years. Demonstrated background and productivity in trauma- and anxiety-related psychopathology research. Proficiency with statistical programming (R, Python, or equivalent). Excellent
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the potential to be a second year pending performance and funding. Your skills will make a difference. You will be working for a university that is internationally recognized for our academic programs and
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. ---- Retirement Plan Eligibility: The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length
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system dynamics and hydroclimate extremes. Strong programming skills including analysis of large hydroclimate datasets in Python or similar and creating analysis and visualization workflows on a