Marie Skłodowska-Curie Doctoral Training Network – Coupled Problems for Decarbonization in Industry and Power Generation (COMBINE)

Construction of a setup with a single rod and a rod bundle Measurements of vibrating rod/rod-bundle using our in-house gamma-tomography system AI-assisted reconstruction and imaging of vibrating rods/bundles using sensors and tomography data Use of machine-learning for noise reduction and data enhancement

The Marie Skłodowska-Curie Doctoral Training Network COMBINE brings together 17 academic institutions and 14 industrial partners across Europe. The network addresses key challenges in fluid structure interaction (FSI) relevant to energy, process, and materials engineering, with a strong focus on advanced numerical modelling and simulation, experimental methods and sensor technologies, data analysis of real-world monitoring data, and artificial intelligence and machine learning for engineering applications. Researchers in COMBINE benefit from interdisciplinary, international, and inter-sectoral training, including secondments at leading academic and industrial partner institutions across Europe.

• Master's degree in engineering, physics, applied mathematics, computer science, or closely related field

• Strong background in mathematics and machine learning

• Programming proficiency in Python, C++ or similar

• Experience with data processing and model interpretation

• Ability to work independently and collaboratively in an international research environment

• Good written and spoken English

• Hands-on experience with experimental setup and basic electronics understanding is of advantage