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Work Week: Standard (M-F equal number of hours per day) Posting Position Title: Research Specialist University Job Title: Data Scientist Preferred Education, Experience and Skills: Ph. D. in a quantitative field like Economics, Physics, Statistics, Mathematics, Data Science, Engineering, Health Policy or related fields.
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We are hiring a Senior Statistical Analyst to leverage cutting-edge data science tools and methodologies on real-world clinical data for scientific research in precision medicine.
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The inaugural Senior Associate Dean of Public Health Data Science and Data Equity, Anna Lauder endowed Professor of Biostatistics, Professor of Chronic Disease Epidemiology, Professor of Statistics and Data Science, with a focus on creating and maintaining software packages, providing user support and training in coding and software package writing, and providing statistical analysis for research projects.
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As a representative of the library, interact with various groups involved in biomedical informatics research and clinical and other healthcare data, such as the Section of Biomedical Informatics and Data Science and the Joint Data Analytics Team.6.
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Responsibilities include but, are not limited to:· Work across functional areas to assess oncology reporting requirements, determine the optimal visualization strategies, and then collect, analyze and present quality improvement data for purposes of Institute-wide program evaluation, management/decision-making, clinical quality improvement, and regulatory compliance.
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The post will be based in the Department of Department of Computer Science and also involve working with the Division of Informatics, Imaging & Data Science. Prof Frangi is the Bicentennial Turing Chair in Computational Medicine at the University of Manchester, Manchester, UK, with joint appointments at the Schools of Computer Science and Health Science.
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Assist in the warranty claims process in the field by sending data and information to the Warranty team/Customer Service Department. We use our expertise in materials science to engineer and manufacture high-quality, sustainable residential and commercial building products that improve lives and businesses.
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Required Qualifications Qualifications must include an earned doctorate in Mathematics as well as the ability to teach a wide range of mathematics and/or statistics/data science classes at the undergraduate level in more than one area of specialty.
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Master’s degree or PhD in information science, computer science, engineering, library science, ontology, semantics or computational linguistics. Bachelor’s degree in information science, computer science, engineering, library science, ontology, semantics or computational linguistics.
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This role will be part of a diversified analytical team, whose aim is to expand new and upcoming data science and predictive methodologies, to provide strategic market insights that enable effective, data driven decision-making for business units, while staying closely aligned to brand strategy and priorities.
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Ability to teach hands on graduate courses in general areas of data science such as artificial intelligence, deep learning, distributed & scalable data engineering, machine learning, and natural language processing.
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PhD (or equivalent degree) in statistics, biostatistics, data science, computational biology, bioinformatics or related discipline with a minimum of 3 years relevant work experience, or Masters with a minimum of 6 years relevant work experience.
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Utilize data from Achievement First's interim assessments to drive instruction and intervention. Attend all professional development, team planning and data analysis meetings. Science Teachers' salaries range from $49,378-$75,149, based on experience.
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Description Yale University’s Statistics and Data Science (S&DS) Department invites applications for three faculty positions to start at the Associate Professor with tenure level or Full Professor with tenure level to start in July 2024.
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With our philosophy based in the science of Applied Behavior Analysis, we use evidence-based instruction and data-based decision making to design, analyze, and modify all interventions in order to maximize student success.
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