Topic: Surrogate Models

Develop Bayesian calibration methods that explicitly represent model error in structural dynamics. The PLATON team will compare informative calibration quantities, implement and benchmark algorithms, and accelerate inference with surrogate models. The work aims to improve finite-element predictions under uncertain material, boundary and loading conditions. Applicants need a relevant doctorate and scientific-computing expertise, with experience in structural dynamics, model calibration or uncertainty quantification. Appointment: 12 months; advertised start 2027-01-01. 2788€ gross/month.