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on the design and development of power electronics, active harmonic filters and advanced control systems. The position is supported by Michigan Translational Research & Commercialization (MTRAC) Advanced
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Qualifications* PhD in Computer Science or Engineering, Biomedical Engineering, Neuroscience, Bioinformatics, or other relevant field. Experience with machine learning and statistical analyses. Proficiency with
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Bioinformatics, as well as the Departments of Biostatistics & Biomedical Engineering, University of Michigan is seeking a postdoctoral fellow for bioinformatics problems involving quantum machine learning and
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education, patient care, community service, research and technology development, and through leadership activities in Michigan, nationally and internationally. Our mission is guided by our Strategic
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% - Ultrasound Data Collection and Data Analysis 30%-Conference Abstract and Manuscript Preparation Required Qualifications* PhD in Mechanical Engineering, Electrical Engineering, Computer Science, or related
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) PhD graduate who is interested in strengthening their experimental, analytical, and publishing skills before transitioning to independence within academia or bio-pharma industry. Transferring
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tissue engineering approaches. The ideal candidate will have comprehensive knowledge and strong interest in pursuing musculoskeletal biology and/or microphysiological systems, with a willingness and track
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Medicine improves the health of patients, populations and communities through excellence in education, patient care, community service, research and technology development, and through leadership activities
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or professional degree graduates or junior postdoctoral trainees in an engineering, life sciences, physical sciences or a related field. A PhD or professional degree must be granted prior to starting the fellowship
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Qualifications* PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related field Familiarity with (biomedical) signal processing Experience working with clinical data