259 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" positions at Stanford University in United States
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scientists, and machine learning experts will be an essential and enriching component of the position. Strong candidates will have a background in machine learning and natural language processing (NLP), with a
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one or more of the following areas is a BIG PLUS: data science (machine learning and AI), cancer biology, animal physiology, organic chemistry, E3-ubiquitin biology, and gene editing. In all cases
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. 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
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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
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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
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skills. * Proficient computer skills and experience with office software and email applications such as Microsoft Office, Adobe Acrobat, etc. * Proficiency in content management systems (e.g. AEM, Website
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Stanford University, recognized as one of the most prestigious and innovative academic institutions in the world, has an opening for an Office Manager & Executive Assistant in the Department of Learning
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patients requiring urgent or emergent intervention. The fellowship provides comprehensive training in data engineering, exploratory analysis, statistical modeling, machine learning, and artificial
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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, use a
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connectivity and graph-theoretic analyses Familiarity with MR sequence programming (Siemens or GE platforms) Machine learning / AI applied to neuroimaging data EEG acquisition and analysis Use of neuroanatomical