-
learning and simulation-based inference for searches for dark matter (or other “invisible” new physics signals) at the Large Hadron Collider, with the support of competent and friendly colleagues in
-
in large pre-trained models (vision-language models), generative models (flow matching, diffusion), simulation-based inference, and robust and active learning. The group has a wide network of
-
through the department’s involvement in engineering and master’s programs. Our research and teaching are conducted within seven divisions with different research focus. Read more about us here About the
Enter an email to receive alerts for process-simulation "DIFFER" positions