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engineering to develop cutting-edge AI technologies for patient care. One critical area in need of advancement is the integration of radiology images (such as MRI and CT scans) with pathology images, which
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to lab operations and maintenance Participate in team meetings and present research findings to internal and external stakeholders Minimum Qualifications PhD in Chemical Engineering, Materials Science
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Minimum Qualifications Candidates must have a PhD and proven research experience in computation analyses, statistics, mathematical modeling, or engineering. Prior experience in Ophthalmology research is not
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at the University of Utah. Qualifications: The candidate should hold a PhD degree in Biomedical Engineering, Physics, or a related field, and have demonstrated excellence in medical imaging research, as evidenced by
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: To be considered, applicants must possess a PhD, PharmD, MD, or doctoral degree in a related discipline, currently have secured funding, demonstrate authorship, and have a program of research. Preferred
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behavioral treatment programs and public health prevention efforts (i.e., policy and nutrition assistance programs). Minimum Qualifications A PhD in public health, implementation science, behavioral science
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Associate to join our team investigating fundamental questions in ribosome biology. Our research is centered on understanding the mechanisms of protein synthesis and translational control in health and
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protocols; assess for clarity and subject safety Review and understand inclusion/exclusion criteria Screen clinic schedules for potential study participants and healthy control participants Carry out study
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advancement. The ideal candidate will have a PhD in computer science or related field utilizing computer science methods, strong expertise in medical image processing, registration and analysis and a long-term
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transformation. Exposure to statistical analysis, data engineering, and data visualization using tools such as SQL, Python, R, Tableau, Excel, and Power BI is expected. Experience with machine learning and data