21 modal-analysis-machine-learning Fellowship positions at University of Texas at Austin
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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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one or more of the following areas: (1) modeling of infectious disease dynamics, (2) statistics, machine learning, and AI, or (3) operations research and optimization. Preference will be given
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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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have been received within the last three years, 1 year of experience with machine learning, natural language processing, AI tools and frameworks, data integration, and/or explainable AI. Proficiency in
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from date of hire. Preferred Qualifications Aptitude and experience with: (a) predictive machine and deep learning techniques, (b) statistical analysis, (c) hands-on experience using models such as
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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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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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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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Retirement contributions Paid vacation and sick time Paid holidays Please visit our Human Resources (HR) website to learn more about the total benefits offered. Purpose Planet Texas 2050 is currently seeking
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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