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Field
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Department:Radiology Salary Salary:$50,004.00 to Commensurate Position Details Full/Part Time Status:Full Time Percent Time:100% Position Description: Post-Doctoral Research Fellow in Quantitative Brain Imaging The MR
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related field. The ideal candidates will have experience in one or more of the following topics: deep learning for image and point cloud data processing, deep learning for time series data prediction
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and ex vivo cellular imaging, bioinformatics, production of genetically engineered animal models, single-cell profiling, and advanced image processing and analysis. In addition, numerous institutional
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magnetic resonance imaging using pulse sequence design, image reconstruction, and real-time image processing, for brain, body, and fetal applications. Responsibilities: The successful candidates will develop
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engineering, medical physics, or related fields, with proficiency in preclinical MRI, image data processing and analysis. Experience in handling and working with rodents is preferrable. Baylor College
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Description Post-Doctoral Fellow Position in Medical Image Processing (Deep Learning for Trauma CT) The Trauma Radiology AI Lab (TRAIL) in the Department of Radiology & Nuclear Medicine at the University
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Computer Engineering Position Summary Application Deadline Applications screening will begin immediately. However, screening of applicants will continue until the position is filled. Starting date
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at the molecular level. Our experts in various platform technologies, such as: radiochemistry, nanotechnology, polymer, synthetic chemistry, optical imaging, medical physics, antibody, biology, engineering, and
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, materials science and engineering, chemical engineering, or in a relevant engineering field, with an extensive background and training in the operation of a wide range of spectroscopic and imaging techniques
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Scale Tissue Atlas" project. -Duties include conducting research on image processing, image alignment, and instrument design and development for the funded projects. -This project will require expertise