267 machine-learning "https:" "https:" "https:" "https:" "https:" positions at Stanford University
Sort by
Refine Your Search
-
verbal and written). Ability to understand and follow job-related instructions given in English, either verbally or in writing. Basic computer skills(email/Calendaring) and use of smart phone Basic
-
*: Frequently stand, walk, twist, bend, stoop, squat and use fine light/fine grasping. Occasionally sit, reach above shoulders, perform desk based computer tasks, use a telephone and write by hand, lift, carry
-
light/fine grasping. Occasionally sit, reach above shoulders, perform desk-based computer tasks, use a telephone and write by hand, lift, carry, push, and pull objects that weigh up to 40 pounds. Rarely
-
computer tasks, use a telephone and write by hand, lift, carry, push, and pull objects that weigh up to 40 pounds. Rarely kneel, crawl, climb ladders, grasp forcefully, sort and file paperwork or parts
-
for international education. Your primary responsibilities* include: Advising and coaching MBA student leadership teams as they design and deliver Global Study Trips using experiential learning principles
-
, linguistics, communications, and the biological, natural, health, and computer sciences. The Center has a distinguished history of fellowship support for individual scholars and research projects through its
-
, experiential learning, integrated education, and connection opportunities, our faculty, staff, alumni, and employers teach through their real-life stories and empower trainees to define and tell their own. Job
-
financial information. Advanced proficiency in business applications, such as Microsoft Office suite, especially Excel. Demonstrated knowledge of financial systems; internet and computer literacy. Knowledge
-
communication skills, thrive in a team-oriented environment, and have a strong desire to learn. Duties include*: Schedule and/or call subjects for appointments; contact participants with reminders or other
-
outcome to transcranial magnetic stimulation (TMS) in depressed patients. Using machine learning, our projects seek to maximize this EEG biomarker and improve the efficacy of this treatment. The candidate