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methods for coordinating fleets of EVs during large-scale emergency evacuations under energy and infrastructure constraints. To address this challenge, the research will leverage reinforcement learning
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and reinforcement learning for real-time optimization, fault self-recovery, and production scheduling in industrial processes. Publish research results in top-tier international conferences and journals
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learning (RL) and deep reinforcement learning (DRL) for autonomous process management, dynamic resource distribution, and real-time decision-making. Design and deploy digital twins for integrated chemical
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scientific achievements in the field of reinforced concrete structures; • Ability to model structural elements in nonlinear analysis software (preferred Atena); • Documented experience in other software
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for improving the safety of LIBs Reinforced polymer composites In-depth understanding of the fire behaviors of materials for LIBs The candidate will acquire hands-on experience with flame retardancy, and polymers
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required. The nature of the duties are such that they require knowledge of an advanced type in a field of science or learning, are predominantly intellectual and varied in character, and require consistent
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mental disorders across development. We develop and apply mechanistic models (e.g. reinforcement learning, normative modelling), generative approaches to augment neuroimaging data, and digital twin brain
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: ● Applicants must have a PhD in Computer Science or related field, with no more than five years post receipt of the PhD. ● Experience in one or more ML domains, such as deep learning, reinforcement learning
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ML domains, such as deep learning, reinforcement learning, or human-centered ML. Proficiency in programming languages (e.g., Python) and ML frameworks (e.g., TensorFlow, PyTorch), with evidence in
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following is an advantage: Multimodal interaction analysis, eye tracking, speech analysis, or affective computing; VR-based experiments or immersive interaction; Adaptive dialogue management, reinforcement