313 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at University of Texas at Austin
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inpatient internal medicine services. Candidates with a strong background in cardiology is preferred. The faculty member will be expected to supervise pharmacy students and residents to help them learn how
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of fundamental programming concepts and the ability to teach pseudocode interpretation and coding basics across various languages. Dynamic communicator capable of creating and delivering engaging, motivational
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dynamics, (2) statistics, machine learning, and AI, or (3) operations research and optimization. Preference will be given to candidates with knowledge of infectious disease epidemiology, strong coding skills
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to supervise pharmacy students and residents to help them learn to care for hospitalized pediatric patients with acute and chronic conditions. The successful individual will have interests in developing
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Bachelor’s degree in engineering, computer or information science, or other applied sciences. Experience designing acoustic sensors or autonomous underwater vehicles. Candidate must have parametrically modeled
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. Hands on mechanical or electrical skillsets including soldering, machining, and/or assembly work. Ability to read and understand technical drawings. General Notes An agency designated by the federal
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in dismissal. Purpose Educational Coaches (ECs) are activity and pedagogy experts for the GeoFORCE field academies. They ensure students are learning and work as a team with a lead summer coordinator
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of the position. Preferred Qualifications Bachelor's degree in Computer Science or Electrical/Computer Engineering. Minimum of three years of experience in Microsoft Office 365 administration and cloud technologies
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) Flexible spending account options for medical and childcare expenses Robust free training access through LinkedIn Learning, plus professional conference opportunities Tuition assistance Expansive employee
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and wave phenomena. Experience designing and tuning dynamic systems for sensing applications. Experience with linear dynamic system analysis and advanced computer modeling using finite elements