32 computer-science-intern "https:" "https:" "https:" "https:" "U.S" uni jobs at Stanford University
Sort by
Refine Your Search
-
Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 08-Feb-26 Location: Stanford, California Type: Full-time Categories: Staff/Administrative Internal Number: 108179
-
; statistical methodology such as missing data, survival analysis, statistical genetics, or informatics; statistical computing; database design (e.g., expertise in RedCAP or MySQL); graphical techniques (e.g
-
; statistical methodology such as missing data, survival analysis, statistical genetics, or informatics; statistical computing; database design (e.g., expertise in RedCAP or MySQL); graphical techniques (e.g
-
represent data to internal and external audiences, client groups, and all levels of management. Strong analytical and problem-solving skills to review and analyze complex information. Advanced computer
-
. Ability to routinely and independently exercise sound judgment in making decisions. Demonstrated experience working independently and as part of a team. Relevant computer systems/technology experience
-
for this position. Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa. About Us The Stanford Doerr School of Sustainability
-
government leaders around key technology challenges. Translate outcomes from convenings into Executive Summaries, internal strategy documents, and external briefings. Professionalism: Ability to represent
-
. The Stanford Vision and Learning Lab (SVL) at SAIL within the Computer Science Department addresses the theoretical foundations and practical applications of computational vision. We are focused on discovering
-
Department. Computer Science website: https://cs.stanford.edu / Within the Stanford Artificial Intelligence Lab (SAIL ), the Stanford IRIS (Intelligence through Robotic Interaction at Scale) focuses
-
. The Stanford Vision and Learning Lab (SVL) at SAIL within the Computer Science Department addresses the theoretical foundations and practical applications of computational vision. We are focused on discovering