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studies. Develop and apply advanced statistical methods and machine learning techniques using tools such as R and Python. Integrate and run process-based models (e.g., crop models, hydrologic models
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symptoms across the healthcare system, by integrating neuroimaging, psychophysiology, and computational modeling. Our work spans from basic science to clinical/translational neuroscience with humans, and our
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science, information science, data science, (bio)-statistics, (applied) mathematics, physics, or a related STEM fields. Strong programming and data analysis skills (e.g., Python, R) Solid understanding of machine learning, deep
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. Experience with statistical characterization of data, preferably within a Bayesian framework. Preferred Qualifications: Experience developing a (semi-)independent scientific research program on topics in
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year to support professional development (e.g., travel to workshops or national conferences, purchase of education materials). Minimum Requirements: PhD degree in computer science, statistics
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: Ph.D. in Geography, Geology, Oceanography, Coastal Engineering, Earth Science, Computer Science, or a closely related field Strong programming skills in Python (preferred), Matlab, or R Demonstrated