The successful candidate will work on next generation molecular simulations and neural network potentials with the goal of substantially impacting physics-based simulations and molecular dynamics.
These positions involve having a key role in the development of OpenMM (http://openmm.org ) of which we are co-coordinators. The candidate will contribute together with other PhDs fellows and international collaborators from academia and industry to the research lines of the Computational Science Laboratory (https://www.compscience.org/ ).
Depending on your skillset, you are expected to contribute to the machine learning of neural network representations for molecular potentials, improve speed in collaboration with OpenMM and Nvidia, enhance capabilities in terms of representing longer range physical terms, charges, etc.
Relevant publications: TorchMD: A deep learning framework for molecular simulations, S Doerr, M Majewski, A Pérez, A Krämer, C Clementi, F Noe, T Giorgino, … Journal of chemical theory and computation 17 (4), 2355-2363 (https://github.com/torchmd )
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