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funding, including with writing technical portions of grant proposals. Required Qualifications* A doctoral degree in epidemiology, sociology, health behavior, health policy, statistics, or a related field
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research, as evidenced by publications, training, and proficiency in statistical analysis. The fellow should have a career trajectory in the field of social epidemiology, cognitive aging, dementia, and/or
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science research institution in the world. This interdisciplinary community includes researchers from sociology, anthropology, economics, psychology, information and computer science, statistics, geography
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, computational and statistical genetic and bioinformatic methods implementation; vascular biology research using in vitro and in vivo models of cardiovascular diseases, particularly those that disproportionately
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factorization and other core signal processing concepts Expertise for data analysis and statistical evaluation inMatlab, C++, and Python High-performance computing skills Background Screening Michigan Medicine
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communication skills. The ideal candidate will use their computational skills, biological knowledge, understanding of statistics, and creativity to help us understand complex genomic data sets. Proficiency in
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the world. This interdisciplinary community includes researchers from sociology, anthropology, economics, psychology, information and computer science, statistics, geography, public policy, public health, and
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publications and present findings at professional meetings. A collaborative, curious, proactive and organized temperament. Desired Qualifications* Desired qualifications considered a plus: statistical training
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* ? Knowledge of control theory, statistical and probabilistic methods, optimization, machine learning, robotics, or related fields. ? Passion for water, the environment, and open source. ? Strong
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proposals Statistical or data processing, data integration Assist with the dissemination of research findings Participate in research meetings as necessary Programming (10%) Participate in cohort-based