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motivated Postdoctoral Associates to join our research team in the field of AI for Precision Medicine and Therapeutics. They will work on developing Artificial Intelligence (AI) and network data science
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interaction, adapt to new tasks, and generalize across environments. Dexterous Manipulation – Advancing robotic grasping, in-hand manipulation, and adaptable object handling in complex real-world scenarios
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models to analyze and mitigate fine particulate matter (PM2.5) exposure from various infrastructure systems (e.g., transportation networks, manufacturing systems, and truck routing). Assessing
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the study of the development of singularities, the long-time behavior of complex systems, the formation of spatial patterns, the transition between stability and instability, and the first steps of transition
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and implementation of incentive mechanisms for sociotechnical and cyber-physical-human systems, with particular emphasis on smart mobility and urban transportation networks. In particular
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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adaptable object handling in complex real-world scenarios, including those involving deformable objects and uncertain conditions.. Semantic Navigation & Mapping – Designing solutions for robot navigation
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models to analyze and mitigate fine particulate matter (PM2.5) exposure from various infrastructure systems (e.g., transportation networks, manufacturing systems, and truck routing). Assessing
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addressing complex challenges. Responsibilities will include writing reports, authoring publications, drafting patents, and presenting results at conferences. The ideal candidate will possess demonstrated
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: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design Creating and validating digital twin architectures that incorporate physical laws and constraints