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Field
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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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. Proficiency in programming languages like C and Python, as well as deep learning frameworks such as PyTorch and TensorFlow. Knowledge in imaging and computing device and equipment. Strong communication
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learning algorithms (Deep learning, Reinforcement learning, etc.); Proficiency in written and spoken English - essential for data analysis and communication with stakeholders Excellent oral communication
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, Artificial Intelligence, Data Science, Computational Biology, Biomedical Engineering, or a related discipline. Strong research expertise in machine learning, deep learning, or computational modeling with
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, algorithmic, AI and communication skills. Proven track records of working in rapid R&D environment with wealth of experience in path planning for robotic arms, reinforcement deep learning and AI. Good
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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | 17 days ago
completed projects, preferably with publicly available repositories. Experience with deep learning frameworks such as PyTorch and JAX. Hands-on experience in developing and training deep learning models
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candidates will have a PhD or equivalent in a relevant discipline and experience in the development of machine/deep learning (ML/DL) methods for engineering and will use this experience in collaboration with
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turbine engines. Successful candidates will have a PhD or equivalent in a relevant discipline and experience in the development of machine/deep learning (ML/DL) methods for engineering and will use
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of causal reasoning tools, including causal inference, counterfactual analysis, causal discovery. Development of deep learning methods on computer vision. Job Requirements: Preferably PhD in Computer
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develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. General information about the position. The position is a fixed