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Field
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computational models, systems, and AI/ML tools using algorithms and analytics for materials and related physical sciences for a broad range of energy, transportation, and advanced manufacturing applications. In
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, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and
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will have a strong background in wireless communication, signal processing, and machine learning. They should also possess the skills necessary to develop complex models, algorithms, and simulations
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systems in firmware algorithm development and simulation. We are also active in R&D using AI in custom electronics as well as in distributed computing. The Pitt ATLAS Group is led by Professors Joe Boudreau
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identify those with the highest potential for early adoption in space engineering; translate theoretical advances into algorithmic innovations, design principles and prototype tools that can be integrated
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supercomputer. The role includes developing and advancing open-source software for large-scale hyperparameter optimization (HPO), neural architecture search (NAS), and Bayesian optimization on distributed HPC
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for communications metrics Hardware-aware evaluation (desired): participate in SDR/hardware-in-the-loop experiments and help bridge algorithm design with realistic RF/platform effects. Required qualifications Ph.D. in
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 8 days ago
. Description: Atmospheric ozone is multi-faceted in that it is protective or harmful to life on Earth depending on its proximity to life. Thus, it is very important to accurately know the vertical distribution
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), custom accelerators, and next-generation quantum and analog devices. Your work will contribute to a vision of autonomous system engineering in which AI agents understand algorithmic intent, architectural
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simulation tasks. Develop and maintain HPC-ready software workflows for distributed training, large-scale inference, scalable data ingestion, and data management on leadership-class computing systems and