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of manuscripts, presentations, and grant materials Participate in lab meetings and contribute to the scientific discussion Qualifications: PhD in Neuroscience and Pharmacology, or other related disciplines Prior
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written, • Strong understanding of mixed-methods research with proficiency in quantitative data analysis and statistical methods (e.g., SPSS, R, STATA, or similar software) and experience with qualitative
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of stability and change in major social institutions and the implications for formal and non-formal education. This course is not taught electronically or online. Location: STBIO S3/3 (please note that course
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. Qualifications: Minimum of one year post-PhD experience in a research/academic position or industry position working on development of AI-based solutions for heavy industrial machines. Extensive code-base
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Statistics (CRNs: 3050/3051) Course Description Principal methods, models, and hypothesis-testing procedures for the prediction and analysis of patterns, structure, and relationships in multivariate data (e.g
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analysis software and methods and willingness to learn new data analysis techniques and brain imaging methods are assets. This position is covered by the AMURE collective agreement: https://www.mcgill.ca/hr
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Supervisor: Joann Whalen, PhD Department of Natural Resource Sciences Macdonald Campus; McGill University Position Summary: Use modern digital communication techniques to engage stakeholders interested in soil
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manuscript preparation and contribute to scientific publications and conference presentations. Supervise and train graduate and undergraduate students in data analysis and field methods. Required
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community. A demonstrated commitment to equity, diversity, and inclusion is also expected. Qualifications and Education Requirements Candidates must: Hold a PhD or a medical degree; Have formal research
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publications and presentations. • Conduct statistical analysis for ongoing BCU projects using appropriate software and methods. • Implement FDA and Health Canada regulations as needed. • Serve as a