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challenge and translates research insights into real-world impacts through strategic outreach and training for the next generation of global energy leaders. EPIC’s pre-doctoral fellowship program serves as a
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research projects with an emphasis on image analysis and computational pathology and the development of AI-driven data pipelines. The ideal candidate is a motivated individual with strong programming skills
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of Chicago Booth School of Business, the Kenneth C. Griffin Department of Economics, the Harris School of Public Policy, and the Law School. The Predoctoral Research in Economics Program (PREP) is intended
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using supervised and unsupervised machine learning/deep learning techniques for various research applications. Design and implement NLP algorithms and techniques for text preprocessing, feature extraction
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research activities, assists in preparing human subjects protocols, manages and analyzes data across multiple projects. Contributes to building traditional statistical models and machine learning algorithms
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algorithms for clinical processes in the transplant program and more broadly in the Section of Pediatric Hematology/Oncology & Stem Cell Transplantation. Coordinates transplant research protocol development