10 results for Climate
Discovering physics extremes with computing
Mathematics and algorithms for identifying configurations of complex physical systems exhibiting unique, anomalous properties.
Auto-omics for climate and sustainability
An automated explainable bioinformatics and AI workflow for multi-omic, climate and environmental data, applied to sustainability problems e.g., nature-based carbon capture.
Incremental machine learning for extreme scale computing
AutoML for incremental machine learning algorithms for big time-series data.
Accelerated discovery of battery materials
Leveraging our expertise in materials science, AI, quantum and high performance computing, we're developing a more powerful, sustainable, and energy-efficient battery.
Sustainable replacements for PFAS
We're addressing the environmental and human health impact of PFAS ‘forever chemicals’ by accelerating the discovery of sustainable replacements and improved capture materials.