Sort by
Refine Your Search
-
to function studies in the context of human genetics of complex traits and generating large data sets for collaborative science. The PI is committed to training and mentoring and will provide exceptional
-
primary research areas: 1) statistical inference in high-dimensional and large-scale testing scenarios; 2) the development of novel model architectures for large-scale proteomics data; and 3) causal
-
/artificial intelligence; (f) health policy, health economics, and decision science; (g) and implementation science Eligibility The ideal candidate will have an MD/DO, PhD, or ScD. PhDs/ScDs may be in clinical
-
external) is reimagining the experimental neuroscience pipeline with big data and AI at its core. A central goal of the project is to build a foundation model of the visual brain—a “digital twin” that
-
disease, including AI-powered tools and new statistical techniques that leverage large datasets, heavy computational capabilities, and/or a robust understanding of biological systems to provide unique
-
population-level outcomes. Utilize advanced quantitative methods to analyze large healthcare datasets, including Medicare and Medicaid claims (MedPAR, Outpatient, Carrier, TAF). Develop reproducible code and
-
, publications and experience presenting data at national and international meetings Names and addresses of 3 academic references. One of these must be your main PhD supervisor. Stanford is an equal opportunity
-
spatial and temporal monitoring results in enormous volumes of data, necessitating the management of large datasets and communication of extensive (and expensive) data packets. These factors necessitate new
-
expertise in Neuropixels or other large-scale in vivo electrophysiology techniques. An expert neural data analyst may be considered even with minimal animal experience. Required Application Materials: Cover
-
graduates of PhD programs in statistics, economics, computer science, operations research, or related data science fields. The position provides opportunities to participate in rigorous, quantitative research