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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Fellowship in Reinforcement Learning and Autonomous Laboratory Systems Department Research | Tang | Michael Smith Laboratories
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be advantageous. Proven track record in research and development of edge intelligence algorithms will be advantageous. Knowledge of machine learning or reinforcement learning techniques will be
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disorders can be better recognised and treated more efficiently. About the role We are looking for a Research Fellow to join the RELMED project aiming to understand which computational (reinforcement learning
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control and reinforcement learning Power system operations, planning, and electricity market design Transportation systems modeling and optimization Responsibilities: Postdoctoral fellows will: Develop
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, shaping the future of medicine through cutting-edge research. A Postdoctoral Fellowship position is available in the RSP Lab led by Dr. Sklavenitis Pistofidis. The RSP Lab (https://rsplab.org ) leverages
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Reinforcement Learning Research area 2: AI-Enhanced Digital Twin Framework for Smart and Sustainable Advanced Manufacturing Research area 3: Advanced Multifunctional Materials The ideal candidates would have a
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infrastructure, with the state-of-the-art reinforcement learning and generative AI, to detect, prevent, and preemptively mitigate intelligent attacker vectors. Supportive Mentoring: The postdoc will be guided by
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be advantageous. Proven track record in research and development of edge intelligence algorithms will be advantageous. Knowledge of machine learning or reinforcement learning techniques will be
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Transparency, and Societal Impact. Candidates should bring expertise in areas such as: Causal inference and the design and analysis of experiments Reinforcement learning and sequential decision-making Analysis
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mathematical background in reinforcement learning and/or control (e.g., optimal control, decentralized control, and/or adaptive control) with a strong desire to make an impact on energy/power grids are preferred