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twins are leveraged to develop paradigm shifts in quality assurance, quality control, real-time process control, and design optimization for the United States. In this digital environment, you will use
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electron microscopy, advanced image analysis and programming (e.g., scripting in Digital Micrograph, Matlab/Python). This full-time position is available as early as fall 2025, for a period of one year with
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analysis using the Digital Signal Processing (DSP) toolbox in MATLAB (including novel analyses), and data visualization via YAEL (Your Advanced Electrode Localizer). The successful candidate will also have
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research areas include Biomedical applications, Communication systems and information theory, Digital systems and computer architecture, Microelectronics, Micro-electromechanical systems (MEMS), Nano
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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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environmental conditions. Our lab is equipped with state-of-the-art facilities, including multimodal laser-induced shock waves, terahertz spectroscopy and imaging, high-resolution and high-speed digital image
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: Performs specialized research techniques and procedures related to phenotypic characterization of cardiovascular disease using available signal-based and imaging techniques. Compiles and analyzes data using
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programming; experience in Python for machine learning and/or digital image processing is preferred. Strong communication skills, both in formal written reports/manuscripts and oral presentations. Language
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
imaging, and structured electronic health record (EHR) data. The postdoctoral researcher will work closely with the Director for Cardiovascular Artificial Intelligence Research and contribute to the design
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robust 3D imaging technique suitable across diverse scientific communities. This project has two interconnected aims. The first is to create an accurate “digital twin” of the experiment through end-to-end