Many researchers and engineers view mechanical fatigue of metals as a stagnated field, evidenced by the lack of substantially novel design approaches against fatigue in recent decades. However, our current capability to investigate, probe, and model the multiscale mechanisms of fatigue damaging processes may turn out to be pivotal for next-generation paradigms for the assessment of fatigue.
Structural Integrity and MEchanical Design (SIMED) group is seeking a 17-month full-time Postdoctoral Researcher (or Associate Researcher, not holding a PhD) in Computational 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.
A POSTDOC OPPORTUNITY is available in my research group to work on structural integrity assessment using physics-guided machine learning and fracture-based computational methods. The position is fixed-term for 1 year, with commitment for the submission of a proposal in the framework of the MSCA Global Postdoctoral Fellowship 2023
Only nationals or long-term residents of the EU Member States or Horizon Europe Associated Countries can apply
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.
The project focuses, but not limited to, on feasibility study and application of Machine Learning methods to applied and numerical fatigue fracture mechanics problems.
Materials Today Communications (MTCOMM) call for papers
Special Issue on Advanced Welding and Joining Technologies
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).
