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Field
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, measurement techniques, and algorithms in support of applications from a broad user base. This role resides in the Advanced Detection and Applied Data Science (ADADS) group, Nuclear Structure & Advanced
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analyses, develop diagnostic, prognostic, and predictive models using different types of data (e.g., exposure data, omics data, and clinical data), and develop algorithms and methodologies for evaluating
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research projects, including: carrying out statistical and bioinformatics analyses, implementing algorithms for genomic analyses, developing computational workflows, and building visualization tools. As part
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require expertise in both database design and complex statistical methods and algorithms. Expected projects will include design of research and operational databases and statistical analyses, and
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submission to journals and conferences. Present research findings at seminars, conferences, and scientific venues. Develop innovative and robust machine learning algorithms to personalize interventions
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judgment, completing tasks with minimal supervision. Capable of identifying and solving complex problems involving multiple stakeholders. Experience managing daily deadlines and long-term projects. Able
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Cornell faculty members and the project’s co-principal investigators (from multiple organizations) to oversee a cross-organizational research team consisting of a group of postdoctoral associates, PhD
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on biomedical research. This department leads multiple federally and non-profit funded biomedical research projects, which are focused on the integration, analysis, and sharing of biomedical and health care data
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to contributions in top-tier international journals and real-world implementations. Responsibilities: Develop and refine algorithms for decision optimization and risk control, utilizing big data and advanced
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, and the willingness to work with multiple researchers, and technical staff in an interdisciplinary environment; Must be able to exercise judgment and discretion, and to prioritize and manage multiple