PhD Candidate in AI-assisted asset management of coastal infrastructure

Descrizione

PhD Candidate in AI-assisted asset management of coastal infrastructure Sintesi in italiano (traduzione automatica): L'Università NTNU cerca un candidato per un dottorato di ricerca in gestione patrimoniale assistita da intelligenza artificiale per infrastrutture portuali. La posizione è situata a Ålesund e prevede lo sviluppo di una piattaforma di valutazione dei rischi e della resilienza per porti selezionati, utilizzando ispezioni con droni e dati storici di gestione patrimoniale. Il candidato collaborerà con il dipartimento di ingegneria strutturale e gruppi di ricerca internazionali, contribuendo a progetti di ricerca in corso. È richiesta una laurea in ingegneria civile o un campo correlato. Il progetto mira a migliorare la resilienza delle infrastrutture portuali in risposta ai cambiamenti climatici, utilizzando un modello di intelligenza artificiale per la classificazione automatica dei danni strutturali. This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three cities with headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position Climate change influences the magnitudes and return periods of heavy rainfall, storm surges, landslides, and many other stressors and shocks with dire consequences for civil infrastructure. The research group within civil engineering focuses climate resilient infrastructure using measurement data to support the assessment of the resilience of critical infrastructures in waterfront communities. Fjordlab Ålesund is an important and rapidly growing sensor and observation platform that contain a wealth of data in the domain of met-ocean, stormwater system, water supply system, structural systems, energy systems, ecosystem, acoustics and more. This position aims to develop a hazard and resilience assessment platform for selected ports focusing on AI-empowered asset management using drone inspections and available asset management historical data. The aim is to enhance the asset and network resilience of ports by training an AI model on ferry quay data and in turn apply it to generic port structures. The position will be in close collaboration with the Structural Engineering department at NTNU, international research groups and directly involved in ongoing research projects at the department. The candidate will also play an important role in strengthening the interdisciplinary collaboration across NTNU. Are you motivated to take a step towards a doctorate and open up exciting career opportunities? As a PhD Candidate with us, you will work to achieve your doctorate, and at the same time gain valuable experience that qualifies you for a further career in higher education and research, in and outside academia. Your immediate leader will be the Head of Department. About the project The candidate will be working on the project ”AI-empowered asset management for port structures”. Norwegian ports are critical infrastructure — vital to national logistics, maritime trade, and the livelihoods of coastal communities. Yet unlike roads and bridges, most port structures fall outside any regulated asset management system: there are no common inspection guidelines, no shared database of structural condition, and no systematic basis for assessing how resilient these assets are to hazards. As climate change drives increases in extreme weather, storm surges, and flooding along the Norwegian coast, this gap is becoming increasingly consequential. This PhD project addresses that challenge head-on by developing an AI-powered asset management framework for Norwegian port structures. The approach leverages the BRUTUS database — Norway's national asset management system for ferry quays, containing labelled damage data as training material for a machine learning model capable of automatically classifying structural damage from drone inspection images. The project aims to bring automated, cost-effective damage detection to port structures that have historically lacked any formal monitoring. The research is anchored at the Magerholm Research Quay (MRQ), a unique full-scale laboratory established as part of Fjordlab Ålesund through a collaboration between Møre og Romsdal County and NTNU. MRQ provides unparalleled access to real-world structural and operational data, including met-ocean conditions and ferry impact loads — an ideal testbed for developing and validating the AI and drone-based inspection methods at the core of this project. The project is funded by the Faculty of Engineering and a collaboration between the Department of Ocean Operations and Civil Engineering and the Department of Structural Engineering. Duties of the position Complete the doctoral education until o Annuncio in inglese. Fonte: Euraxess (Commissione europea).