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successful candidate is required to: • Contribute to Robust Splatting, Dialogue, Speech Signal Processing and Machine Learning algorithms. • Contribute to Image Processing and Machine Learning algorithms
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geophysical survey and machine learning algorithms. Mainly responsible for processing geophysical/geomechanical data and analysing the data using machine learning. Conducting research, supervising undergraduate
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detection algorithms for cracks, chokage, deformation, corrosion, etc. Establish datasets, annotation standards, training pipelines, and benchmarking protocols for ML models. Integrate uncertainty estimation
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to publications in top-tier international conferences and journals, as well as real-world implementations. The role includes designing novel algorithms, building robust software systems, and collaborating with
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reliability evaluation under bending, stretching, and cyclic deformation. Collaborate with interdisciplinary researchers to integrate soft-interconnect solutions into stretchable electronic devices, sensors
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novel algorithms for efficient, high-fidelity 3D scene reconstruction and representation, including applications in embodied environments where an agent must continuously perceive, update, and reason
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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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-driven researchers with a strong grounding in behavioural epidemiology, digital health, or related disciplines to contribute to innovative research at the interface of wearable and sensor-based health
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that capture interactions between device characteristics, circuits/systems behaviours and algorithm performance. Qualifications • Min bachelor’s degree in Electrical Engineering, Computer Engineering or
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implement VLA models and world models. Develop and optimize deep learning algorithms to enable robotic arms to perform complex tasks guided by natural language instructions. Utilize PyTorch to train and fine