We are not accepting applications for this position at the moment. Candidates have been pre-selected for this position, pending final interviews and recruitment decision.
Project Title: Mapping corrosion around marine structures using corrosion sensors (WP1)
Host Institution: Antwerp Maritime Academy (HZS)
Supervisor: Geert Potters (PhD promoter, Antwerp Maritime Academy)
Objectives: To use a set of widely used sensors for the physicochemical environment of such a structure, as well as a machine learning algorithm to assess corrosion risk, before the damage has been inflicted.
DC3 will outfit a mobile unit with these sensors for autonomous or remote measurement of the corrosion risk in a seawater environment. DC3 will test the unit on different marine locations (calibrating the unit using existing data sets) and create a corrosion risk heat map of these locations. DC3 will optimize deployment (in terms of data storage/transfer, energy use, autonomous operation, …) for further validation of the mobile sensor unit to assess corrosion on an underwater industrial structure such as a seaweed farm. DC3 will employ machine earning methods to develop a corrosion risk algorithm. DC3 will gather data for model development and training at different marine locations (Southend Pier (UK), Blue Accelerator (BE) and a seaweed farm on the Irish coast or in the North Sea.
Expected Results: Algorithms allowing autonomous drones to assess the onset of corrosion on submerged marine structures.
Enrolment in Doctoral degree(s): Antwerp Doctoral School
Host: SPG, Supervisor: Rahimeh N. Monemi, Timing: M15-17, Length: 3 months, Purpose: testing and validation of systems to measure and predict corrosion risks and rates around marine infrastructures (such as seaweed cultivation setups).
Host: C-CUBE, Supervisor: Guus Coolegem Timing: M28-31, Length: 4 months, Purpose: training in machine learning as a research tool in offshore applications
- You hold a master’s degree in mechanical engineering, materials engineering, nautical sciences or a related field and you thrive in a multidisciplinary research environment.
- You have a solid knowledge of sensors, machine learning and their application in real-world environments.
- You are ambitious, well organized and have excellent communication skills.
- You speak and write fluent English and have the ability to work effectively and collaboratively.
- You are an enthusiastic and motivated person, ready to participate in personal training, international travel and public awareness activities.
- You have demonstrated your commitment to high quality research.