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Ultrasound (UDUS) Research Group and the Michigan Institute for Imaging Technology and Translation (MIITT) at the University of Michigan. Our team is positioned at the interface of ultrasound (US) and magnetic
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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
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Specialist Intermediate position. The successful candidate will contribute in a variety of ways, consistent with her/his existing skills and previous experience in support of clinical and preclinical imaging
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blot, immunofluorescence) Cell transfection Mechanical testing and biomaterials characterization Quantitative image analysis Computational skills including data processing and statistical analysis Prior
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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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of Orthopaedic Surgery is conducted by a diverse group of faculty, staff and trainees with expertise in biology, engineering, health outcomes, and healthcare. Our research teams are focused on improving treatment
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Galban, focuses on developing and establishing mouse models of various malignancies recapitulating human disease to develop novel therapies, including gene therapy and imaging technologies. Central to our
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to investigate these questions including murine models, human T cells, flow cytometry, molecular biology, biochemistry, imaging and bioinformatic analyses. The position is in the interdisciplinary and
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conferences. Participate actively in writing manuscripts and grants. Required Qualifications* BS in an Engineering field 5+ years of experience with imaging in cancer biology Expertise with MATLAB computer
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into the design of a prototype implant to be tested in large animals. The Neural Engineering and Ophthalmology research environments are excellent. The Neural Engineering Training Program and the Vision Research