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will work closely with interdisciplinary researchers and engineers to develop novel AI algorithms, publish in top-tier venues, and translate research innovations into real-world sustainability solutions
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implementation novel machine learning and large language model (LLM) algorithms for Green AI applications. Support the research of efficient AI techniques, including model optimization, parameter-efficient fine
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support the development, simulation, testing, and implementation of collaborative control algorithms for multi-agent robotic systems, under the guidance of the PI and senior researchers. The work will first
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perception, mapping, obstacle avoidance, and multi-agent path-planning algorithms, and integrate these capabilities on physical drone platforms. The work will involve system integration, simulation, hardware
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grow. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. Key Responsibilities: The development of new algorithms
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learning-based model predictive control (MPC) algorithms for multi-agent multirotor drone navigation around vessels in maritime environments. The role will focus on integrating multirotor crash predictions
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localization algorithms, spearhead energy-aware navigation planning systems development, and oversee real world validation of underwater navigation technologies while mentoring junior team members. Key
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Localization and Perception System based on Multi-sensor Fusion Job Description: Responsible for development of robust and reliable sensor fusion algorithms for localization and navigation algorithms of robot in
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at the intersection of algorithmic guidance and management. These issues have become more pressing as generative AI offers potential productivity gains while also making it easier to conceal effort. A first study
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sustainable manner. Key Responsibilities: Responsible for developing explainable machine learning algorithms for Tunnel Boring Machine (TBM) tunnelling and excavation Developing large language model enhanced