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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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Research Assistant 2 position is based in Prof. Tal Arbel's research lab in the department of Electrical and Computer Engineering. This position provides research, technical, and administrative support for
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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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untrained data points. QUALIFICATIONS: Experience in neural-network-based architecture Familiar with Stellantis Familiar with machine learning methods and techniques for data analysis Strong analytical and
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. Kwofie, Bioresource Engineering Position Summary: (1) Technical Development:(a) Design and implement machine learning models using Python, TensorFlow, PyTorch, and Keras for predictive analytics and
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approved, McGill University Education/Experience: Expertise in coding in Matlab, Python or other computational languages as well as with neural networks, machine learning, Markov models and other
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digital communication protocols, and applying advanced Digital Signal Processing (DSP) and Machine Learning algorithms on embedded systems. The Research Assistant 2 will report to the McGill Principal
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to the research project or academic research experience. -Experience working in health research, bioinformatics, applied advanced machine learning models. -Superior computer skills Hourly Salary: $29.21 Hours per
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and clean socio-economic and demographic data for Quebec Run a series of spatial regression and machine learning models on the data; Geospatial analysis running a series of spatial regression models