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selected as one of Canada’s Best Diversity Employers and a Greater Toronto’s Top Employer for 2015, 2016, 2017 and 2018. To learn more about our work environment, colleagues, leaders, students and innovative
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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] Subject Areas: Computational Biology / Data Analytics Machine Learning / Machine Learning Analytical Chemistry / Current Advances in Chemistry & Biochemistry Computational Science and Engineering
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Full-time: 35 hours per week Fixed-term: 31st March 2026 The School of Informatics at the University of Edinburgh invites applications for 2 Post-doctoral Researcher positions in Quantum Machine
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methodologies generally, machine learning techniques, OR complexity analysis/nonlinear dynamics are particularly well-matched to the opportunity, but applicants with theoretical expertise related to compact
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methodologies generally, machine learning techniques, OR complexity analysis/nonlinear dynamics are particularly well-matched to the opportunity, but applicants with theoretical expertise related to compact
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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from varied sources, and machine learning methodologies Required Application Materials: 1. A cover letter describing: a. Your interest in this position b. Your relevant training and experience c. Your
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. Ready to be part of our team? Let’s shape the future together! About the team: The Computational Materials Discovery group is looking for a postdoctoral researcher working in the field of machine learning