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Field
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Summary The Center for applied research is seeking a motivated PhD student in Data Science to support ongoing projects focused on data-driven forecasting and spatial analysis. This position is ideal
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control Strong background in machine learning and data-driven modeling for engineering systems Experience with scientific programming (e.g., Python, MATLAB) and numerical methods Proven ability to conduct
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assigned. DESIRED QUALIFICATIONS: * Possess a MS and/or PhD in a STEM field with a computational component. * Be comfortable manipulating data sets, particularly large timeseries ones. * Be comfortable in
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with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications
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, statistical modeling, machine learning, and big data computing for public health professionals. The program is designed for working professionals, with classes held remotely during the week, and in-person one
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to contribute to one or more projects, learning advanced cellular and molecular biology and anaerobic microbiology techniques. The candidate’s day will be split between benchwork to generate data, and computer
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machine learning models. Working with extremely large, multi-modal datasets. Prior experience in analysis of clinical health records, and time series data are highly preferred. Qualifications Requirements
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responsibilities? No Preferred Education/Experience Bachelor’s degree in Computer Science, Machine Learning, AI, Data Science, Engineering, Mathematics, or related field (Master’s or PhD preferred). 7+ years
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research, machine learning or artificial intelligence (e.g., large language models, EHR foundation models), causal inference (e.g., target trial emulation), and child health research. The research program
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and enthusiastic individual who meets the following criteria: Recently earned a Ph.D. in bioinformatics, computational biology, computer science, electrical and computer engineering, or a related