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: Machine learning/deep learning model development for biomolecular data analyses and prediction Research Area: Data science and computational chemistry Required Skills: A Ph.D. in relevant field within
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Council of Canada). The research will focus on applying, developing, and implementing novel statistical methods for causal inference, integrative data analysis, and machine learning with large
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contribute to the collaborative TQT research community. Principal Investigator: Na Young Kim Project Name: Solid-state analog Optimization Solver and Quantum Machine Learning (Theory) Research Area
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and synthesize relevant literature in machine learning, representation learning, and manifold learning. Propose and implement extensions to existing dimension reduction algorithms using contrastive
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project on convergence analysis of reinforcement learning algorithms for partially observed environments. The position is at the intersection of machine learning, stochastic analysis, and dynamical systems
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with strong background in Computer Vision and Machine Learning. Position Overview: In this position, you will investigate the existing solutions for assessing datasets and developing a novel tool relying
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We are looking for a motivated undergraduate student research assistant to join our project to enhance the safety of underground mine personnel. This project focuses on developing machine learning
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McGill University | Winnipeg Sargent Park Daniel McIntyre Inkster SE, Manitoba | Canada | about 5 hours ago
fluorescence data. Developing machine learning methods to optimize data collection. In addition, the project is committed to developing open source tools that benefit the imaging community. The applicant will
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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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, Indigenization, internationalization, student wellness, undergraduate competencies, and other teaching and learning priorities. Your general location of work will be remote, with the use of your own reliable