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Field
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skills and strong publication records to apply. Some skills in analyzing/evaluating large data sets are highly desirable. Knowledge of an advanced programming language such as MATLAB, Python, etc. is
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applicable. Preferred Qualifications PhD in data science, and/or public health or related fields including health services research, health informatics, computer science. Experience in data analysis using
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to manage, organize, and back up large amounts of image and tabular data generated by program and collaborator labs. Other Requirements: -May have to work on the weekend and/or after normal hours. -Travel is
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statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data, including physiological waveforms and medical imaging. We foster a collaborative and
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Position Details Position Information Recruitment/Posting Title Postdoctoral Associate Job Category Staff & Executive - Research (Laboratory/Non-Laboratory) Department CINJ - Pediatric Hematology
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to submitting your application, please review and update (if necessary) the information in your candidate profile as it will transfer to your application. Job Title: Post Doctoral Scholar - Surgery Department
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learning, decision-making, belief updating) Coordinating large database of computational task data for harmonized analyses Modeling individual differences and within-person change over time in a longitudinal
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, select, and apply standard techniques of routine research. Keep detailed records of data. Use computers and laboratory or technical equipment to perform data analysis, statistical analysis, and technical
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. Participate in analyzing and disseminating data results as part of participation in group meetings. Prepare manuscripts, periodic reports, scientific papers/presentations, and grant proposals. Provide advice
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data and develop data-driven methods for predicting land loss and ecosystem transitions in wetland-rich landscapes of the Gulf Coast with a focus on coastal Louisiana. This candidate will directly