Marie Sklodowska-Curie Actions Doctoral Network BlueOcean

id="offer-description" class="ecl-u-type-heading-2 ecl-u-mt-none ecl-u-mb-l">Offer Description This PhD aims to develop novel robotic monitoring and data processing methods to document changes in dynamic seafloor environments over large spatial scales. Motivation: Understanding how the seafloor evolves is critical for environmental monitoring and subsea infrastructure inspection. Natural processes and human activities drive changes over time, yet detecting these reliably remains challenging. Improved methods could enable early identification of risks to ecosystems and infrastructure, while providing quantitative evidence to support effective intervention and adaptive management. Challenges: Documenting change in GNSS-denied subsea environments presents significant challenges. While changes occur over large spatial scales, change is often gradual, meaning that between seasonal or yearly deployments, the magnitude of change at any point on the seafloor remains below to the detection limit of even high-resolution mapping sensors. In addition, recognising and aligning scenes across repeated surveys is difficult due to navigation drift, evolving scene structure, and sensitivity to environmental conditions. Research questions: . How can evolving seafloor scenes be consistently recognised and spatially aligned across repeated subsea surveys in GNSS-denied environments?. How can small seafloor changes be reliably detected when they are comparable to sensor noise?. How can full-field