276 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" "U.S" positions at Stanford University
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knowledge in bioinformatics, machine learning, statistics and programming skills (R, Python, or MATLAB) are required. Record of peer-reviewed publications. Knowledge in one or more of the following areas is
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tasks, use telephone, write by hand, lift, carry, push and pull objects weighing over 40 pounds. Occasionally sit, kneel, crawl, reach and work above shoulders, sort and file paperwork or parts. Rarely
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, 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 kneel, crawl, climb ladders, grasp forcefully, sort and file
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business applications, such as Microsoft Office; intermediate Excel skills. Demonstrated knowledge of and experience with accounting systems and the internet; computer literacy. Understanding of and ability
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, machine learning, statistics and programming skills (R and Python) is preferred. Record of peer-reviewed publications. Knowledge in one or more of the following areas is desirable: single-cell profiling
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-year fixed term 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
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excellence and values innovation, collaboration, and life-long learning. To foster the talents and aspirations of our staff, Stanford offers career development programs, competitive pay that reflects market
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to apply theoretical knowledge of science principals to problem solve work. Ability to maintain detailed records of experiments and outcomes. General computer skills and ability to quickly learn and master
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to curriculum deployment, participant engagement, program evaluation, and alumni engagement. The role requires expertise in learning management systems, online course development, faculty engagement, program
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Quantum Fundamentals, ARchitectures and Machines program (Q-FARM) is an interdisciplinary initiative woven throughout the university. Q-FARM harnesses the expertise and facilities of Stanford University and