272 parallel-computing-numerical-methods positions at University of Kansas Medical Center
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quality of care for our patients. Our Division is active in research which includes NIH-funded grant studies as well as institutional and industrial collaborations. Our program boasts an ACGME accredited
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research program seeks to increase our understanding of the immunological and molecular mechanisms involved in autoimmune dysregulation in Type 1 diabetes (T1D). Through the use of novel murine models
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with Dr. Colby Souders and assist the urology research program manager, Jane Ledesma, with research activities. This position provides research support for Dr. Colby Souders research projects
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of animal enrichment program. Assists investigators and their research staff with training needs. Administers training sessions for researchers and LAR staff. Prepares quotes for surgery and supplies; submits
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forms are obtained prior to any research activities. Utilize evidence-based practice methods to improve participant care and study conduct. Able to be flexible with daily assignments including work
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). Assist with modifying computer scripts dedicated to analysis tasks. Prepare manuscripts and assist in grant preparation. Attend and participate in IBIC meetings. Maintain a current Laboratory Notebook
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participants, completing all required tracking and documentation Identify barriers to program enrollment and participation Promote evidence-based health promotion and risk reduction strategies related
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, the Recruitment Assistant must have a personable demeanor and be comfortable interacting with a variety of personalities via many methods of communication (phone, email, mail, etc.). This Recruitment Assistant role
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, the Department has access to exceptional SOM resources to support diverse community engagement and recruitment, quantitative analytics and health informatics. Opportunities abound for collaboration through KUMC’s
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. Experience with cell culture and sterile technique Prior experience as a research technician or lab manager Skills: Familiarity with standard molecular biology techniques and/or immunological methods Excellent