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Field
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aims to investigate how network intelligence and automation, distributed core network designs, and AI-driven control loops can improve network robustness, service continuity, and fault tolerance across
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the development of autonomous, snake-inspired robots capable of robust locomotion across complex and uncertain environments. Drawing inspiration from biological snakes, the research combines soft and flexible
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towards sustainable flights. However, there are significant challenges in achieving net zero. This project will explore approaches to achieving robust control of the electrical power system for aircraft
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that maintain stable operation under variability, recover quickly from disturbances, and remain reliable in remote, harsh, or unpredictable conditions. This demands optimized system sizing, robust control
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robust control methods Controllers for underactuated and coupled robotic dynamics Stability-aware and model-based autonomy ROS/ROS2-based autonomy development Real-world testing on aerial, underwater, and
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problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control
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is to develop RL methods that can search large policy spaces and support decision-makers in exploring robust strategies under deep uncertainty. Policy problems typically involve many control levers
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be considered an advantage if you have experience with safety-critical systems, multi-agent autonomy, or learning-based/data-driven/robust/adaptive control under uncertainty, supported by strong
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robustness, fairness, and accessibility. You will design and run reproducible experiments, measure relevant resource metrics, implement prototypes in Python, and communicate results through publications and
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to antibiotics are rising. This doctoral research project aims for localized delivery of beneficial microbiomes to support robust healthy biofilm development. The project encompasses (i) electrospinning and