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statistical modeling approaches. Support the integration of implementation science methods to improve the translation of research findings into clinical practice. Assist in the development of guidelines and
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Women’s Hospital (Boston). The fellow will collaborate with research staff in the development of the necessary analytic files, lead the statistical analyses, and prepare manuscripts for publication
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Council of Canada). The research will focus on applying, developing, and implementing novel statistical methods for causal inference, integrative data analysis, and machine learning with large
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Minimum Qualifications - PhD in ecology, remote sensing, environmental sciences, or a related field - Strong quantitative skills, including ecological data analysis, statistical analysis and data management
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swine research, statistical data analysis, feed formulation with Brill software, and quantitative research techniques, as well as have excellent communication and writing skills. In addition
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sciences, data science, mathematics or a related field - Strong quantitative skills, including data analysis, statistical modeling and data management - Proficiency in R and/or Python programming - A proven
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with multivariate statistics, machine learning, and/or remote sensing would be an asset. Experience and education: Ph.D. degree in geography, agriculture/agronomy, environmental science, or a related
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record; a strong background in computational and/or experimental techniques, such as programming (R, Python), statistical modeling, conducting online experiments (Prolific, Gorilla), and acoustic analysis
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, remote sensing, environmental sciences, data science, mathematics or a related field - Strong quantitative skills, including data analysis, statistical modeling and data management - Proficiency in R and
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data analysis, statistical analysis and data management - Proficiency in R and/or Python programming - An interest in interdisciplinary research spanning ecology, remote sensing, spatial analysis and