272 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" positions at Stanford University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
reports to the Assistant Director of Administrative Learning & Development, Department Liaison. Stanford Law School, on the campus of one of the world's leading research universities, offers unmatched
-
commitment of mutual respect, the idea that every member of the staff has something to contribute, and that learning is constant. We seek a team member who is ready to share their skills and perspectives
-
Website: https://med.stanford.edu/stankovic-lab.html (link is external) https://hellerlab-stanford.net/ (link is external) How to Submit Application Materials: Please send the following materials in a
-
complete the Stanford application process and submit their CV and letter of interest thru the Stanford Careers website - https://careersearch.stanford.edu/ referencing job number: 108273. The expected pay
-
Appointment Start Date: Immediately Group or Departmental Website: https://med.stanford.edu/lulab.html (link is external) How to Submit Application Materials: Email the required application materials to bingwei
-
. Minimum Knowledge, Skills and Abilities Required: General understanding of scientific theory and methods. General computer skills and ability to quickly learn and master computer programs. Ability to work
-
records of experiments and outcomes. General computer skills and ability to quickly learn and master computer programs, databases, and scientific applications. Ability to work under deadlines with general
-
and/or cutting edges machine learning techniques to make foundational discoveries in reproductive medicine. The annual salary for this full-time position starts at $76,383, dependent upon skills and
-
individuals who are passionate about science, learning, and collaboration. Candidates with a strong background in molecular and cellular biology, and/or experience in bioinformatics, will find this an ideal
-
and patient-reported outcomes; (b) observational research and comparative effectiveness studies; (c) intervention studies; (d) clinical informatics, mobile/electronic health; (e) machine learning