enrico.salvati1's blog

I would like to draw your attention to our recently proposed predictive method based on a semi-empirical model (LEFM) and Neural Network, exploiting the Physics-informed Machine Learning concept. We show how the accuracy of state-of-the-art fatigue predictive models, based on defects present in materials, can be significantly boosted by accounting for additional morphological features via Physics-Informed Machine Learning.

Structural Integrity and MEchanical Design (SIMED) group is seeking a PhD candidate to conduct research in computational solid mechanics, mainly applied to structural problems. The successful applicant will work at the Polytechnic Engineering and Architecture Department (DPIA) of the University of Udine, under Dr Enrico Salvati’s supervision.

Structural Integrity and MEchanical Design (SIMED) group is seeking a 1-year full-time Postdoctoral Researcher in Machine Learning applied to fracture mechanics. The successful applicant will work at the Polytechnic Engineering and Architecture Department (DPIA) of the University of Udine, under Dr Enrico Salvati’s supervision.

I am seeking a full-time Postdoctoral Research Fellow in Phase-Field modelling of fracture to join the Design of Machines group at the Polytechnic Engineering and Architecture Department (DPIA) of the University of Udine. The position is fixed-term for 1 year with funding provided by the European Social Fund (ESF).