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research has been funded by multiple NIH R01 grants and industry grants with awards from AAPM and ASTRO. Dr. Ren is a Fellow of AAPM. Details about Dr. Ren’s profile can be found at the following link: https
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) delivers capabilities to government customers for multiple applications, from on-site real-time data-intensive underwater acoustic signal processing to standalone remote field systems. ESL is seeking a
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, image processing, prototyping, test, analysis, and evaluation. Support field-testing of imaging systems. Contribute to proposals, reports, and presentations. This position can be filled at multiple levels
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software is not on the blacklist" (without revealing the exact software). There are multiple aspects of this project. For all aspects, some cryptography background is required. Design and analysis of new
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Science in the Grainger College of Engineering at the University of Illinois invites applications for multiple full-time teaching positions to support the continued expansion of our teaching activity
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employment. Vaccine Protocol Position Summary/Purpose of Position: The Department of Computer Science is looking to hire multiple instructional faculty members, at the rank of Lecturers, Senior Lecturers
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images. However, the current limitations of desktop computers in terms of memory, disk storage and computational power, and the lack of image processing algorithms for advanced parallel and distributed
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
Nutrition Research Institute (NRI) is a world-renowned center and a global leader in precision nutrition research. Our on-site facilities include multiple wet labs and clinical facilities as well as a
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Anomaly detection is an important task in data mining. Traditionally most of the anomaly detection algorithms have been designed for ‘static’ datasets, in which all the observations are available
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systems. This work will specifically focus on combining ML algorithms with classical data analysis and control techniques to develop robust in situ (i.e., in real-time, during the operating experiment