-
this project to propel discovery of how recent advances in AI can promote healthy aging and longevity around the world. The general aim of the work is to study how new LLM-type modeling architectures can be
-
-world needs. Finally, the postdoc will participate in disseminating research findings through presentations, talks, and publications. Mentorship Structure The postdoctoral research scholar will be
-
study of ECE and policy impacts. Strong data analytical skills using advanced statistical methods (such as mixed effect models, multilevel modeling, structural equation models, longitudinal modeling, etc
-
at Stanford University uses computational systems modeling to advance resilient and equitable water resources management for an uncertain future. Current research topics in the lab include: adaptive planning
-
also help with grant writing to get practiced in the skill of academic fundraising that will be vital for their future career. Mentorship Structure The postdoc will be a member of IPRL in
-
research optimizing advanced water treatment processes (e.g., reverse osmosis) to reduce costs and emissions while providing safe resilient supply. They should have documented experience with a variety of
-
environmental stimulants. We employ an interdisciplinary approach to probe, model, and predict how signaling network dynamics translate extracellular cues sensed by GPCRs into specific phenotypic outputs
-
that promote high quality healthcare. Our projects apply advanced analytical methods to large databases of primarily structured electronic health record data and EHR usage metadata. The position will have the
-
analytical methods in large databases, which include claims data and electronic health record data in conventional structures and in common data models. Our research group prioritizes a collaborative and