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Field
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profiling (e.g., flow cytometry, ELISA) Experience with statistical analysis software (e.g., GraphPad Prism, R) for immunological data interpretation Prior publication record in peer-reviewed journals related
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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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relevant programming languages (Python, Perl, R). A good understanding of molecular biology, genomics experiments and bioinformatics is expected. Candidates with proven track record in terms of publications
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cleaning datasets from recently completed research studies, database management, conducting statistical analyses (SAS or R), review/verification and archival of programs for research manuscripts, and
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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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modeling and simulation tools DESIRED QUALIFICATIONS: Experience using NONMEM, R, Monolix and/or other platforms for analysis of clinical and/or preclinical pharmacology data; development of web-based tools
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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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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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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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well as experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and