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Navigating protein landscapes with a machine-learned transferable coarse-grained model

We are excited to present this work, result of a 4-year big collaborative project: https://arxiv.org/abs/2310.18278 . #MachineLearning a transferable bottom-up protein force field, trained on force data from all-atom MD simulations, using physical priors and graph neural networks.

Oct 31, 2023

CECAM-Psi-k Research Conference 2023

From June 19th to June 23rd, we will be hosting the CECAM/Psi-k conference Bridging length scales with machine learning: from wavefunctions to thermodynamics Talks will be broadcasted. More info will be here soon

Apr 05, 2023

Interview with the Einstein Foundation

Our Professor Cecilia Clementi has been interviewed by the Einstein Foundation. You can read the interview here  (german only).

Apr 05, 2023

Congratulations Dr. Charron

Nick Charron successfully defended his PhD and he is now a postdoc in the group. Congratulations Nick!

Mar 10, 2023