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(iii) complex architectures with tightly coupled components hinder modular adaptation. To address these limitations, we research a physics-guided machine learning framework that integrates physical
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environments This PhD project investigates the use of digital technologies (environmental sensing, user feedback loops, computer vision, machine learning) and theories of human perception and behavioral nudging
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sciences » Philology Chemistry » Physical chemistry Environmental science » Earth science Computer science » Computer systems Computer science » Computer systems Computer science » Computer systems Computer
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researchers from IDLab-AIRO (robotic experts) and imec. Your main tasks include: Reviewing literature on decentralized control frameworks in the domain and machine learning algorithms compatible with
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Science. Commitment to undergraduate and graduate education. Demonstrated expertise in machine learning/deep learning and software development (Python; PyTorch/TensorFlow). Peer-reviewed publications and strong
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collaborative links thorough our collaborative network. The researcher should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely related field. You have an
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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning
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instructors provide assistance to students in their learning process by utilizing all appropriate college resources, materials, facilities, and educational technologies available to complement the teaching and
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., RGB-D, thermal, LiDAR, tactile), universal perception frameworks (e.g., Vision-Language-Action (VLA) models, Transfer Learning, self-supervised learning) that generalise across tasks and scenarios in
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understanding how moving bodies and perception are integrated, we can develop more effective clinical interventions and inspire the next revolution in AI - one that reflects how biological brains learn through