19 modal-analysis-artificial-intelligence Fellowship positions at University of Texas at Austin
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in this position will conduct/lead applied as well as fundamental research in physics-informed Artificial Intelligence (AI) and Machine Learning (ML) methodologies enabling digital twin functionalities
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in this position will conduct/lead applied as well as fundamental research in physics-informed Artificial Intelligence (AI) and Machine Learning (ML) methodologies enabling digital twin functionalities
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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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areas such as data analysis, statistical modeling, machine learning, numerical modeling, or remote sensing Preferred Qualifications A general understanding of ecosystem modeling or ocean circulation
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to candidates with knowledge of infectious disease epidemiology Responsibilities Lead the development and analysis of mathematical models to support the early detection, forecasting, and mitigation of emerging
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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
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the various aspects of clinical and translational research projects, including study design and development, IRB submission, informed consent, data collection and analysis, abstract submission, data
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, translational science, and patient-centered care, contributing to pioneering efforts in integrating multi-modal data for individualized cancer therapy selection. The lab leads multi-institutional projects
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and are also involved in planetary missions and climate modeling. These research projects produce large data sets and require computational analysis and visualization. This position is for one year with
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the hydrology field, including analysis and interpretation of large datasets using various analytical, statistical, and numerical techniques. Contribute to the publication of scientific papers and presentation