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for one year and may be extended, subjected to performance and availability of research funding. Key Responsibilities: Develop state-of-the-art and innovative models and algorithms to improve port and
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Technology (CQST) advances the science and engineering of next‑generation quantum sensors, with core programmes in cold‑atom sensing, quantum photonics, quantum materials, and superconducting sensor
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algorithms for mobile robots. Implement and accelerate visual algorithms for mobile robots on embedded platforms. Develop a visual embedded platform on a mobile robot. Conduct field trials with the robotic
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collection from both experimental and numerical sources, gathering relevant test and simulation data available globally, organizing the collected data to support model and control algorithm development and
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, including diffusion models and reinforcement learning, for navigation decision-making, trajectory generation and adaptive robot behavior. Key Responsibilities: Design and develop navigation algorithms
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team in the development and validation of novel single-walled carbon nanotube (SWNT)-based sensors, with a primary focus on Covalent Organic Framework microneedles (COF-MNs) and nanosensors for nutrient
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algorithms for digital health and AI-driven research projects. Lead technical innovation by exploring and implementing emerging AI methodologies. Support data platform development and retrospective data
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data analytics; Development of marine geophysical survey and machine learning algorithms; Process geophysical/geomechanical data and analyze the data using machine learning; Conduct research, supervise
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instruments such as ADCP, ADV, water quality sensors, and underwater cameras • Analyse and integrate field observations into predictive physical models • Collaborate with interdisciplinary teams including
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mitigation. Ensure mechanical designs are compatible with robotic arms, mobile platforms, sensors, and mechatronic systems, considering payload, reachability, safety, manufacturability, and maintainability