PhD in Robotic Monitoring and Data Processing for Dynamic Seafloor Environments

This PhD position at the University of Southampton focuses on advancing robotic monitoring and data processing techniques to document changes in dynamic seafloor environments. The project aims to address critical challenges in environmental monitoring and subsea infrastructure inspection by improving the detection of gradual changes in GNSS-denied environments. The successful candidate will combine advanced robotic localisation, high-resolution mapping, and machine learning to develop probabilistic models for detecting subtle changes under noise and uncertainty. The work will leverage existing datasets, simulations, and field campaigns, including access to a dedicated deep-water tank and collaboration with industry partners.

• Develop advanced robotic localisation and high-resolution mapping methods for GNSS-denied subsea environments.
• Design and implement machine learning-based feature detection algorithms to align evolving seafloor scenes across repeated surveys.
• Create probabilistic models to detect subtle changes in seafloor landscapes under noise and uncertainty.
• Validate research findings using simulations, existing datasets from the Smarty200 AUV, and new field-collected data.
• Conduct controlled experiments in the Maritime Robotics and Instrumentation Laboratory’s deep-water tank.
• Collaborate with international partners and industry during secondments in Italy and Canada.
• Participate in interdisciplinary training in robotics, sensing, and AI for marine monitoring within the BlueOcean Doctoral Network.