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Field
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Electrical and Electronic Engineering, or related field. Research experience with Artificial Intelligence/Machine Learning/Large Language Model. Publication track record in a series of top tier conference
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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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, train, and validate advanced computational models and machine learning algorithms tailored to complex datasets. Collaborate with multidisciplinary teams including biologists, engineers, and clinicians
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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | 13 days ago
program at The Hospital for Sick Children, University of Toronto, and the Vector Institute. Our research group focuses on developing machine learning-based pipelines that leverage generative models and
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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to revolutionize agriculture in Morocco by combining cutting-edge technologies, including crop growth models, remote sensing data, data assimilation, machine learning, and seasonal weather forecasts. As a
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Responsibilities: To conduct independent research in deep reinforcement learning and large language models. To produce publications in top conferences and journals. To offer guidance and assistance to any students
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to engage with multidisciplinary teams and external partners. Desirable attributes include experience with spatio-temporal models, machine learning, Bayesian methods, and knowledge of environmental exposure
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dependent predictive deep learning models, and physical mechanistic models (thermodynamic and kinetic models etc.). Examples of suitable backgrounds: machine learning, programming, mathematics, physics. You
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models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques and algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly