261 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" uni jobs at Stanford University
Sort by
Refine Your Search
-
certification is preferred. PHYSICAL REQUIREMENTS*: Frequently stand, walk, twist, bend, stoop, squat and use fine light/fine grasping. Occasionally sit, reach above shoulders, perform desk-based computer tasks
-
degree in a related scientific field. KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED): Comprehensive understanding of scientific principles. General computer skills and ability to quickly learn and master
-
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
-
, 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
-
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
-
, 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
-
*: 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
-
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. About Stanford Libraries: Stanford Libraries is a network of
-
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