Sort by
Refine Your Search
-
University. This research opportunity will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including bulk and single
-
interdisciplinary scientific evidence. This program is funded by the U.S. Department of Education's Institute of Education Sciences (IES) , grant number R305B220018, and housed at the Stanford Center on Early
-
/or experience with large-scale data analysis, algorithm development, or computational modeling. Required Qualifications: Doctoral degree in linguistics, cognitive science, psychology, hearing and
-
scientific excellence. Research investigation in population science is essential to ensure that discoveries from molecular medicine and clinical trials translate to routine practice and ultimately decrease
-
to a high-impact global program with a mission to create a healthier world by addressing lead contamination at the source. Project Unleaded conducts policy-relevant research that positively impacts
-
the Cancer Data Science Core at the Stanford Cancer Institute (link is external) , directed by Dr. Summer Han, Associate Professor at Biomedical Informatics Research and co-directed by Dr. Allison Kurian
-
: Pathology Biomedical Data Science Postdoc Appointment Term: 1 year (renewable) Appointment Start Date: As soon as feasible; February 2026 How to Submit Application Materials: Please email the required
-
science, computer science, health or environmental sciences, or environmental economics Experience with causal inference methods, especially fixed-effects regression A demonstrated interest in
-
for publication in scientific journals • Required to communicate well with other scientists worldwide • Candidate should have 3+ years research experience in immunology; additional background in computational
-
experimental animals Experience implementing and optimizing eye tracking, body tracking, and/or visual reality environments Proficiency in Python and scientific computing libraries Familiarity with spike sorting