The new Tayebati Postdoctoral Fellowship Program will support leading postdocs to bring cutting-edge AI to bear on research in scientific discovery or music.
By analyzing X-ray crystallography data, the model could help researchers develop new materials for many applications, including batteries and magnets.
The SPARROW algorithm automatically identifies the best molecules to test as potential new medicines, given the vast number of factors affecting each choice.
Using generative AI, MIT chemists created a model that can predict the structures formed when a chemical reaction reaches its point of no return.
Using machine learning, the computational method can provide details of how materials work as catalysts, semiconductors, or battery components.
This AI system only needs a small amount of data to predict molecular properties, which could speed up drug discovery and material development.
Matt Shoulders will lead an interdisciplinary team to improve RuBisCO — the photosynthesis enzyme thought to be the holy grail for improving agricultural yield.
Computational chemists design better ways of discovering and designing materials for energy applications.
Artificial intelligence, machine learning, and deep learning are now being used in the chemical industry.Machine Learning and Deep Learning are a growing and diverse fields of Artificial Intelligence (AI) which studies algorithms that are capable of au…
