32 computer-programmer-"https:"-"Inserm" "https:" "https:" "https:" "https:" "https:" "https:" "UNIV" research jobs at University of Kentucky
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to 8 hours/day, lifting <30 lbs, may view computer up to 8 hours/day. Shift Generally Monday – Friday, 8a-5p with some flexibility Job Summary This position is designed to have 70% clinical time, 15
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. Technical Proficiency: Skilled in laboratory or clinical research techniques depending on the research focus. Data Analysis: Proficiency with statistical and computational tools for quantitative and
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/Certification Physical Requirements Sitting for long periods of time; extensive computer use; walk with up to 10 lbs. Shift Flexible hours – 10-20 hours per week Job Summary Dr. Aaron Cook is seeking a Research
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), to work on problems at the intersection of biology, medicine, mathematics and computation. The successful candidate will contribute to the development of next-generation learning algorithms to understand
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Evolution and Virtual Archaeology (HEVA) Laboratory. The student will participate in events and laboratory meetings of both groups. Skills / Knowledge / Abilities Knowledge of at least one computer
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. Willingness to learn new skills and work as part of a collaborative research team. Basic computer skills for data entry and organization. Does this position have supervisory responsibilities? No Preferred
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floor to above shoulders up to 25 pounds. Standing and sitting at computer terminals and laboratory bench completing repetitive tasks for extensive periods of time. Continuous working with materials
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new skills and work as part of a collaborative research team. Basic computer skills for data entry and organization. Does this position have supervisory responsibilities? No Preferred Education
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shoulders up to 25 pounds. Standing and sitting at computer terminals and laboratory bench completing repetitive tasks for extensive periods of time. Continuous working with materials requiring personal
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calculations, sample size determinations and statistical analysis plan. 3. Apply machine learning approaches to integrate diverse datasets collected from study participants to identify subtle differences