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, epigenomics, transcriptomics, and proteomics) information. The postdoctoral fellow will develop and refine machine learning methods for analyzing histopathology, clinical, and multi-omics data, collaborate with
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highly impactful biomedical informatics research that presents new innovations in methods and novel findings that inform disease etiology. The candidate should be interested in focusing on multi-omic
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interpersonal and communication skills. While not a must, a strong background in computational methods and/or statistical methods is a plus. Special Instructions Applicants should submit a formal application and
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Director of LISH (Dr. Ramona Pop). The position involves conducting rigorous empirical research using field experiments, large-scale data analysis, and computational methods to advance our understanding
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environmental and agricultural economics topics and methods. Faculty mentors for this program will include Ishan Nath , Anna Russo , Wolfram Schlenker , and Charles Taylor . An important goal of the fellowship is
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date to be determined. Basic Qualifications A PhD related to programming languages by the start date. Experience in machine learning and formal verification. Individuals with a demonstrated track record
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to collaborate with the Department's interdisciplinary faculty —including economists, physicians, and statisticians—on projects that bridge methods, policy, and practice. This role will involve intensive analysis
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—will be essential to the success of these endeavors. Contributions to scientific knowledge may include formal outcome evaluations of innovative services, as well as more basic research that will
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related quantitative field for a one-year Postdoctoral Research Fellow position. This position involves developing new theory and methods at the intersection of causal inference and network science
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—on projects that bridge methods, policy, and practice. This role will involve designing and executing empirical studies of pharmaceutical competition, pricing, and regulation. The fellow will apply advanced