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Position Summary The postdoctoral fellow will develop artificial intelligence applications to support characterization of medical data with a focus on radiology image, radiology reports, and
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working under the supervision of Prof. Jaideep Vaidya (the PI and Director, I-DSLA) to develop and analyze privacy-preserving solutions for biomedical data research, implementing the developed algorithms
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North Carolina A&T State University | Greensboro, North Carolina | United States | about 2 months ago
for assisting the PI in the development and submission of data reports and presentations required by the funding agencies that sponsor/support research activities in the IMPACT Lab at JSNN. These reports require
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for real-world transportation agencies. The Postdoctoral Associate will join a multidisciplinary team of faculty, researchers, software developers, and agency partners, and will support ongoing deployment
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for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section
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. Essential Duties and Responsibilities Neuroimaging data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms. Assist with organizing large
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heavy software development component. The successful candidate will perform research in the application of machine learning (ML) techniques to the finite element method (FEM) in the context of composites
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heavy software development component. The successful candidate will perform research in the application of machine learning (ML) techniques to the finite element method (FEM) in the context of composites
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ecosystem. Research Responsibilities Responsibilities will vary depending on the Fellow’s background, but may include: • Developing machine learning, optimization, or simulation models to improve clinical
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-doctoral Associate will develop algorithms and theory for machine learning methods, as well as implement and apply ML methods to problems in domains such as computational biology and neuroscience. This is a