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ambitious new project on the safe deployment of medical imaging AI. The purpose of the role is to conduct world-leading research on AI for medical imaging. The goal is to develop methodologies and
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experience. Department Summary University Communications drives the University of Oregon’s strategic goals through the development and implementation of comprehensive communications and marketing programs
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advance groundbreaking computational research? If so, Princeton University's Research Computing department is recruiting a Research Software Engineer to join the fast-growing Research Software Engineering
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data
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. CORE JOB FUNCTIONS ● Runs and maintains existing next generation data analysis pipelines. ● Assists senior bioinformatics analysts in pipeline and algorithm development and validation. ● Extracts
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position in statistics, machine learning, and data science. The postdoctoral researcher will be mentored by Professor Yiyuan She and will contribute to the development of innovative statistical methods and
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PhD position on Closed-loop testing for faster and better EM evaluation of complex high-tech systems
that you help us to solve that problem! The objectives are to develop a world-wide accepted new standard for testing large systems in RC, by comparing the newest fast EM sensor systems, comparing performance
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this project, we aim to: Develop real-time ultrasound algorithms to estimate fascicle length in antagonistic leg muscles (tibialis anterior and soleus) in healthy individuals during walking. Translate and
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Computing (e.g., memristor modeling/simulation/manufacturing) and Edge AI related areas (e.g., AI algorithms, AI accelerator, VLSI). Detailed Position Information The Department of Electrical and Computer
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) and the University of California Irvine (UCI). The Research School "Foundations of AI" focuses on advancing AI methods, including energy-efficient and privacy-aware algorithms, fair and explainable