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quantitative skills including ecological data analysis, statistical analysis and data management Experience in R and/or Python programming An interest in interdisciplinary research spanning the fields of ecology
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in ecology, remote sensing, environmental sciences or a related field • Strong quantitative skills including ecological data analysis, statistical analysis and data management • Experience in R
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required as part of the fellowship. Education / Experience Education: Doctorate Degree Field of Study: epidemiology, applied mathematics, statistics, or related fields Work Experience: A minimum of 1-year
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we do have experienced people in the lab to teach procedures if necessary. A proven track record with a minimum of 2-3 first author publications in reputable journals. Experience with statistical
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model workflow, linking multiple sources of biological and ecological information across scales to monitor and model ecosystem and biodiversity change. Advanced skills in statistical programming and
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Canada, whose presence continues to enrich our vibrant community. Position summary The successful applicants will participate and lead research that applies advanced statistical, AI and ML techniques
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designing and analyzing randomized trials and write short software guides to improve findability; Develop new statistical software packages for experimental research in R to fill gaps in existing tools
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, able to work independently and/or in a team environment. Experience in the management of large data sets and complex analyses using R, SAS or other statistical tools will be an advantage. Salary
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discipline Extensive expertise in cell biology (cell culture, microscopy) Expertise in data analysis and statistics Preferred Qualifications Experience with live tissue or 3D culture models is an asset
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discrete mathematics and graph theory, financial mathematics, fluid dynamics, mathematical biology and applied statistics. To learn more, visit www.torontomu.ca/math/ The Faculty of Science especially