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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 27 days ago
application of the estimators to address measurement issues arising in clinical HIV cohort data, surveillance data, and other data sources as needed. Minimum Education and Experience Requirements PhD in
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experience in pig nutrition. Experience in conducting different types of animal experiments. Skills in the analysis of experimental data and the scientific communication of research results. For non
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experience in: Mammalian cell culture. High-performance computing environments. UNIX and Python and/or R. Reverse genetics systems or viral culture. Advanced statistical or computational data analysis
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to join an interdisciplinary project at the interface of single-cell genomics, data integration, and developmental biology. The project focuses on the integration and analysis of multi-modal single-cell
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on physiologic waveform analysis, biomedical signal processing, and computational modeling of continuous clinical monitoring data. The successful candidate will work on projects involving the analysis
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. PREFERRED QUALIFICATIONS Expertise in nutritional epidemiology and diet-related chronic disease research. Experience with causal inference methods, longitudinal data analysis, and advanced epidemiologic
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intelligence, data science, medical physics, neuroimaging, bioengineering, or related disciplines, accompanied by accredited training in machine learning, deep learning, or medical image analysis. Experience: A
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, Computational Astrophysics, Early Universe or Gravitational Physics will be an advantage as well as experience in the analysis or modelling of LSS data, including (but not limited to) galaxy clustering and CMB
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work and documentation and presenting data, results and method development internally and externally, both in written and oral presentations Supervise master’s and/or PhD students to a certain extent
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integration approaches Additional Information Eligibility criteria Mandatory: *PhD in Statistics, or a related field. *Strong programming skills (e.g., R, Python, or similar). *Knowledge of statistical analysis