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Campus in North Austin. Purpose This position aims to advance innovative processing and acquisition methodologies for land DAS and dense surveys, focusing on synthetic modeling, 4D analysis, and seismic
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of hire. Preferred Qualifications Strong data science skills and demonstrated research experience in analyzing data, such as output from regional-scale hydroclimatic models and hydrologic models related
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, led by Prof. Mrinal Sen, engaged in cutting edge research on solving subsurface imaging problems using advanced techniques of full waveform modeling, inversion and uncertainty quantification. The team
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for some laboratory experiments. Purpose As a part of an interdisciplinary, integrated research project, the candidate will contribute to time-lapse seismic and rock physics modeling and perform sand tank
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transfer, fluid mechanics, and interfacial sciences. Experience with experiments and modeling (traditional CFD modeling). Experience with finite element analysis and/or software packages like Comsol or ANSYS
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not limited to using UAV platforms to characterize active fire thermal and gas emissions, improve spreading models and detection algorithms, and assessing post-fire effects. The aim of the project is to
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. The successful candidate would analyze a suite of climate and atmospheric model simulations to understand the related physical processes of tropical ocean-atmosphere interaction and atmospheric teleconnection
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numerical and statistical modeling of natural systems. Working knowledge in programming languages such as MatLab and/or R. Experience with project management and ability to meet project goals in a timely
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plan, execute, communicate, and publish independent research Proficiency in biostatistical analyse Experience culturing and conducting developmental toxicity studies using saltwater fish models exposed
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Al ethics and bias in Al models. The interdisciplinary TIES lab team, consisting of clinical psychologists, data scientists, software developers, and engineers at UT Austin and other universities