81 computer-science-image-processing positions at University of Minnesota in United States
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Informatics (IHI), University of Minnesota, Twin Cities. Dr. Bayat’s team develops highly scalable and computationally accelerated medical imaging and analysis methods to assist in enhanced diagnosis and
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of precision imaging datasets using supercomputing cluster resources. Support students and trainees involved in data processing and analysis. Present novel discoveries at international conferences. Publish
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, computer vision in the Division of Health Data Science (HDS) at the DOS. The position is an annually renewable professional academic appointment. Duties/Responsibilities: ● Risk predictive model for clinical
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job An NIH-funded postdoctoral position is available for a two-year program in the laboratory of Brendan Dougherty within
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BA/BS in Astrophysics, Physics, or Computer Science Preferred Qualifications Experience with Python, and hands-on work with telescopes About the Department School of Physics and Astronomy: https
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Previous Job Job Title Post-Doctoral Associate - Department of Plant and Microbial Biology Next Job Apply for Job Job ID 370096 Location Twin Cities Job Family Academic Full/Part Time Full-Time
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drugs on biology and metastasis of breast cancer and in vivo imaging to monitor response to targeted therapies. Specific responsibilities/duties include: Research – 65%: Conduct research under the PI’s
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Neuroimaging Hub to assist with imaging analysis for MIDB research projects. A successful candidate will have knowledge of a wide variety of advanced statistical and computational techniques, excellent
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and ability to multitask. •Diligence with protocol adherence. •High affinity with working with technology. •Strong computer skills. •Professionalism. About the Department The Department of Psychiatry
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Previous Job Job Title Post-Doctoral Associate - Electrical and Computer Engineering Next Job Apply for Job Job ID 369523 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular