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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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models for treatment discovery and patient-specific decision support. Gain experience in translational research across clinical, academic, and technology domains. Participate in lab initiatives aligned
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multiscale and multiphysics modeling for thermomechanical effects on high performance heat spreaders based on materials such as diamond thin films. Collaborate with experimental groups on characterization
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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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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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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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therapy) on reward circuit function (assessed through functional magnetic resonance imaging; fMRI) and information encoding (assessed through computational models of reward-processing task behavior) under