Doctoral Researcher in Physics-Enhanced Machine Learning for Floating Offshore Wind Digital Twins

The Marine and Arctic Technology research group in Aalto University's Department of Energy and Mechanical Engineering recruits a salaried doctoral researcher in physics-enhanced machine learning for floating offshore wind digital twins, funded by the Research Council of Finland. Floating turbines move in six degrees of freedom under irregular waves and turbulent wind, and their deep mooring lines are costly to instrument, so operators need digital twins that combine hydrodynamic knowledge with sensor data.

The doctoral researcher develops physics-enhanced models that learn the coupled hydrodynamic and structural dynamics of floating turbines from measurements and update in real time, building on Koopman operator theory and dynamic mode decomposition; embeds hydrodynamics (wave excitation, radiation memory, slow-drift motions, mooring dynamics) so the models stay physically consistent across sea states; estimates unmeasured motions and mooring loads; detects early mooring or structural degradation; and quantifies uncertainty with Bayesian filtering and probabilistic machine learning, using potential-flow, CFD and OpenFAST simulations.

The position starts on 28 January 2027 or as agreed, initially as a two-year contract extendable with progress, with a starting salary of about €3,000 per month (gross). Applications are due by 28 December 2026.

Master's degree by the start date in naval architecture, marine, ocean or offshore engineering, mechanical, civil or aerospace engineering, applied mathematics, physics, computer science or a related field; strong linear algebra and a foundation in hydrodynamics or fluid mechanics, structural dynamics, dynamical systems or signal processing; good Python (or similar) programming and genuine interest in machine learning; excellent English (Finnish not required).