85 data "https:" "https:" "https:" "https:" "ASNR" research jobs at Indiana University
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INDIANA GEOLOGICAL & WATER SUR (UA-GEOY-IUBLA) The Survey is charged with conducting geological research; providing geological information, data, and educational outreach; and maintaining physical
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for the initiation, monitoring, completion, and reporting of routine to moderately complex research studies. Organizes and implements data review and analysis. Oversees the proper handling of laboratory specimens
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, monitoring, completion, and reporting of routine to moderately complex research studies. Organizes and implements data review and analysis. Oversees the proper handling of laboratory specimens including
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at the Indiana Clinical and Translational Sciences Institute (CTSI) Clinical Research Center Helps to prepare Institutional Review Board (IRB) materials and other regulatory documents Enters and manages data
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using laboratory machinery and computer programs. Test and set up lab equipment. Collect data and prepare reports based upon established protocols. Attend and participate in departmental meetings. Order
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@iu.edu Additional Qualifications Preferred Qualifications: · Background in cancer immunology or radiation immunotherapy · Experience with multicolor flow cytometry and data analysis · Familiarity with
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the following supporting documents: Letter of application describing research interests and career goals Curriculum vitae Contact information of three references Review of applications will begin immediately with
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letter describing research experience & interests, CV, and contact information of three references. All applications must be submitted through this site. Priority Application Review Deadline Expected Start
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signal processing and both time-series and frequency domain analysis of physiological recordings including ECG and nerve recordings. This data is used to investigate the cardiovascular effects of altered
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, biomarker, and genetics data across multiple studies. Expertise in biostatistics and familiarity with handling multiple data types, both cross-sectionally and longitudinally, are critical for success. IUSM is