62 postdoc-in-distributed-systems-and-controls research jobs at University of Kentucky
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Standing or sitting up to 8 hours/day, lifting <30 lbs, may view computer up to 8 hours/day. Shift Some flexibility, generally Monday- Friday, 8-5 Job Summary This position is designed to have 60-70 percent
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to above shoulders up to 25 pounds. Standing and sitting at computer terminals and laboratory bench completing repetitive tasks for extensive periods of time. Shift Normal shift is 8 hours during weekdays
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• Ability to perform the physical requirements of the position Required License/Registration/Certification N/A Job Summary THE UNIVERSITY OF KENTUCKY, COLLEGE OF SOCIAL WORK (CoSW) is a renowned leader in
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., sitting for long periods of time, some standing or walking and repetitive motion Shift 8-5 Monday – Friday Job Summary Busy Clinical Research operation is looking for a professional and responsible Clinical
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highly desired. Deadline to Apply 10/16/2025 Our University Community We value the well-being of each of our employees and are dedicated to creating a healthy place for everyone to work, learn and live. In
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position will work primarily in the acquisition, processing, and interpretation of recordings of earthquakes, and other natural and manmade energy sources. Fieldwork is required for the position; experience
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, eastern Kentucky, and eastern Tennessee. For more information on the Department of Forestry and Natural Resources click here . The Martin-Gatton College of Agriculture, Food and Environment is a welcoming
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that apply: ☒Sitting at computer work station for long periods of time ☒Standing for long periods of time ☒Risk of back injury from moving/lifting, equipment, or materials ☐Repetitive motion ☒Lifting/Carrying
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Standing or sitting up to 8 hours/day, lifting <30 lbs, may view computer up to 8 hours/day. Shift Some flexibility, generally Monday- Friday, 8-5 Job Summary This position is designed to have 60-70 percent
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). Previous experience processing imaging data from unmanned aerial vehicle (UAV) is desired. Expertise with R or Python will be valued. Previous experience conducting agronomic field experiments is preferred