Amber Machine Learning and Free Energy Simulation Workshop (AMBER2026)

Workshops

When

2026/07/13 - 2026/07/17

Place

DIPC / Faculty of Chemistry (EHU), Donostia / San Sebastián

Organizers

Xabier López (EHU, DIPC), Jose M. Mercero (EHU), Elena Formoso (EHU), Jon Uranga (EHU), Darrin York (Rutgers University), Solen Ekesan (Rutgers University)

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This workshop will equip computational scientists with the knowledge and practical skills to perform robust, accurate, and efficient free energy simulations using the AMBER software suite. AMBER offers an advanced array of free energy simulation and analysis methods with high-throughput enabled by its efficient GPU-accelerated free energy simulation engine. Through a combination of lectures and expert-guided hands-on tutorials, participants will learn best practices and explore the latest features in AMBER, including new enhanced sampling techniques, optimized alchemical transformation pathways, free energy surface and minimum free energy path methods. AMBER further offers a diverse set of generalized hybrid quantum mechanical (QM), molecular mechanical (MM) and machine learning potential (MLP) force fields enabled by interoperable software infrastructure. Free energy workflows provide a framework from which complex networks of simulations can be efficiently set up, executed and analyzed. Emphasis will be placed on driving applications to enzyme design and drug discovery.

More information: https://amber2026.dipc.org/