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photovoltaic generation, hydrogen production, and storage alternatives with microgrid-driven power distribution. Through advanced modelling and optimization techniques, this research aims to identify optimum
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optimisation techniques, machine-learning methods and data-driven modelling. Familiarity with robotics and autonomous-system simulation environments such as ROS/ROS2, Gazebo, AirSim, Unity, or equivalent
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-driven reusability assessment platforms integrating NDT data, machine learning models, and RFID-enabled traceability systems. Prepare and draft technical reports, conference/journal papers, and
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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE
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Vision, Video Understanding, and Multimodal AI. Design AI models for concept-driven video understanding of consumer facial care behaviours. Work with PI and company to develop the AI solution Develop novel
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support the development of AI-driven and data-driven approaches for the discovery and design of functional materials. The role will involve the development and application of machine learning models, high
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-driven surrogate models for real-time reconstruction and forward simulations. Create numerical algorithms for physics reconstruction using sparse data. Implement assimilation pipelines which integrate
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3D mesoscale materials modeling. Position Details: Location: Ann Arbor, Michigan, U.S. Department: Mechanical Engineering, University of Michigan Start date: Flexible; preferred start date of September
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framework for immersive 3D virtual environments, such as Roblox and Minecraft. The engineer will play a key role in building a parallelized, agent-driven exploration system and integrating a multimodal
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following areas: Structural steel or aluminium structures Welding, fabrication, or construction automation Experimental structural testing and instrumentation Numerical modelling and simulation AI/data-driven