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, and associated clinical outcomes. The fellow will be responsible for identifying computational approaches for data selection, processing, and predictions/inference. The expected outcome of the project
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engineering, electrical engineering, computer science, biostatistics, or a related field. Experience in working with an MRI scanner. Experience in developing state-of-the-art Machine Learning algorithms
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of Program & Employment Compliance at compliance@uada.edu . For general application assistance or if you have questions about a job posting, please contact Human Resources at 501-671-2219 or 479-502
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of computer science fundamentals including algorithms, data structures, and object-oriented programming. Proficiency in C/C++ or similar language Working with large codebases Containerization (Docker) and building
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Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Jan 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 44/2025 Is the Job
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Description The School of Physics (https://physics.gatech.edu/ ) at the Georgia Institute of Technology in Atlanta, Georgia invites applications for a Postdoctoral Fellow position in Artificial Intelligence
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
. * Developing computational and algorithmic approaches to understanding the neurobiological mechanism of neurodisorders. * Interact cross-functionally: work with people across the team to find creative solutions
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 22 hours ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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, establish advanced manufacturing routes for these polymers and implement computational algorithms to assist their optimization. The RISE Polymer Lab is dedicated to developing the next generation of robust
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probabilistic models, hybrid numerical approaches, computational algorithms, and integrated software platforms for modeling and managing the interactions among urban infrastructure and environment networks