SISSA Mathlab and Sauber Motorsport are searching for students from Mathematical Engineering, Mathematics, Data Science and Scientific Computing courses. The internship aims to study the efficacy of applying Machine Learning techniques for improving the accuracy of low-cost turbulence models. The approach will be based on a dataset of results obtained from expensive high fidelity models. The final purpose will be the design, the efficient implementation and the testing of an ML improved RANS turbulence model. The activity will be partially carried out as a funded 6 months internship at the partner institution.
Internship opportunity at Sauber Motorsport: Improvement of RANS turbulence modelling capabilities through Machine Learning
Submitted by Marina D'Alessandro on Mer, 18/11/2020 - 11:21