Three PNNL authored papers were accepted as posters to the ICLR 2023 Workshop on Physics for Machine Learning and Workshop on Mathematical and Empirical Understanding of Foundation Models.
SAGE is a high-efficiency genome integration strategy for bacteria that makes the stable introduction of new traits simple for newly discovered microbes.
Variations in burn severity are a key control on the chemical constituents of dissolved organic matter delivered to streams within a single burn perimeter.
Bobbie-Jo Webb-Robertson is a leader with a PhD in decision sciences & engineering systems from Rensselaer Polytechnic Institute and experience in managing complex scientific programs and line organizations. She assumed the role 3/13/23.
A new nano-optical bioimaging technology in development at PNNL enables researchers to watch climate-bellwether microbes exchange metabolites and other essential signals.
A multi-omics analysis provides the framework for gaining insights into the structure and function of microbial communities across multiple habitats on a planetary scale
Machine learning models help identify important environmental properties that influence how often extreme rain events occur with critical intensity and duration.
Gosline works to develop computational algorithms that are uniquely targeted for rare disease work by doing foundational research in model system development. This work can be expanded to all model systems in human disease.
Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.
