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-inspired approaches for modeling, designing, and predicting the response of composite systems. Responsibilities: Develop AI approaches for predictive multi-physics response of composites in Energy
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holding a PhD in chemical, environmental or process engineering, to apply for a full-time post-doctoral fellowship position in the field of water desalination, focusing on the development of an artificial
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configurations in Energy applications. Lead the development of a unique experimental platform for in-situ characterization under environmental loading of laminated structures. Plan and execute research tasks
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healthcare) where deep learning architectures, hierarchical learning models and representation learning can be truly impactful. The group strives to publish in top-tier ML venues such as NeurIPS, ICLR, ICML