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graduate students in disciplines relevant to chemical risk assessment (e.g., toxicology, chemistry, endocrinology, AI/machine learning) and governmental staff presently involved in chemical risk assessment
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recovery. Oversee the collection, processing, and analysis of physiological data from recreational and elite athletes across various exercise protocols. Utilizing machine learning and deep learning
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and graduate students in disciplines relevant to chemical risk assessment (e.g., toxicology, chemistry, endocrinology, AI/machine learning) and governmental staff presently involved in chemical risk
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, policy, energy conversion, new business models, techno-economic and life cycle analyses, machine learning, optimization, AI, intelligent networks, among others. The PDF will join a project studying
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data science, machine learning preferred. - Strong programming skills in R and/or Python required. We invite applications from qualified candidates who share our commitment to employment equity and
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the following fields: Computer Architecture Algorithms and Optimization Health Research Human-Computer Interaction Machine Learning and ML Foundations Machine Perception Natural Language Processing (including
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of this position may include: Single-cell RNA-seq, perturb-seq, and/or other transcriptomic analysis Next generation sequencing and bioinformatics analysis Machine learning/AI Analyzing data and presenting the data
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Institut national de la recherche scientifique (INRS) | Varennes, Quebec | Canada | about 23 hours ago
lead the development of the new proposed NC-ARPES technique and will also have the opportunity to propose new and independent investigations with the state-of-the-art TR-ARPES machine at ALLS
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midlife brain function and cognition. The applicant should be interested in applying multivariate and machine learning neuroimaging methods to the study of how chronological ageing, biological sex, and
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Department: Electrical, Computer and Biomedical Engineering Position supervisor: Dr. April Khademi Contract length: 1 year (with possibility of extension) Hours of work per week: 36.5 About Toronto