| KEYWORD |
Knowledge-informed Machine Learning
Reference persons DANIELE APILETTI
Description The goal is to understand, manipulate, and improve Physics-informed neural networks (PINNs). Through deep learning, these algorithms allow the solution of differential equations.
PINNs are well-known to suffer from many limitations when facing complex systems, then a prominent direction in research is to develop new ways of training them.
The candidate will apply these innovative algorithms to various well-known hard problems to develop new generalized learning strategies.
Deadline 19/02/2025
PROPONI LA TUA CANDIDATURA