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Field
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
qualifications: A solid background in programming using Python, R, or other languages. Teaching and supervision experience at the BSc and MSc level. Interest and experience in developing competitive national and
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for research (e.g. Python, R and RStudio or MATLAB) and using data-driven pipelines with complex bio-behavioural data. Prior knowledge or keen interest in topics at the intersection of experimental psychology
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to the larger community of special education, such as peer-reviewed journals, and national conferences of professional organizations. 10% - Use ASD/EBD relevant measurement tools (i.e., ADOS-2, ADI-R) to identify
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(PVES ) program at Jefferson Laboratory (JLab ), and Simulation studies & R&D for the future Electron Ion Collider (EIC ). For more information, please visit the PI’s website or the group’s nuclear
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above, (ii) all required documents provided. Shortlisted candidates will be invited for a personal or online interview. The Faculty Recruitment Policy (OTM-R) can be seen here . Faculty of Science
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
ability to program (e.g, python, R, and/or javascript). Must have at least some experience working with geospatial data. Preferred Qualifications, Competencies, and Experience Ability to develop impactful
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preferred. Knowledge of statistical methods, programming (e.g., Python, R), and data quality assurance techniques. Proven ability to work collaboratively in an interdisciplinary environment and engage with
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, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles of climate/weather model output are advantages
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superb quantitative background, strong coding skills (e.g., Python, R), expertise in infectious disease modeling across multiple pathogens, expertise with large datasets and statistical analysis, and high
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programming in, for example, R or Python. Particularly valuable is a research background in ecology, biodiversity, systems biology, or related areas, as well as experience working with time-series data, dynamic