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developing machine learning surrogates and emulators for dynamical systems. Proficiency in managing large datasets and training with GPU-enabled computing resources. Expertise in numerical optimization and
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, and network optimization for 6G networks and FutureG wireless networks. Successful candidates will have the chance to work with top-notch researchers from both academia and industry on future wireless
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simulations and multiscale spatial-omics data. • Integrate uncertainty quantification into scientific machine learning workflows and optimize the design of computational (ABM) and wet-lab experiments
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., VAEs, GANs, transformer-based models) to large-scale biomedical and biological data, including developing and optimizing models to predict disease progression and create realistic patient profiles
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system optimization for remote construction. This position will focus on advancing research in construction assembly science and technology, logistics optimization, and real-time communication frameworks
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 hour ago
, and create personal and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our vision is to be
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
experience programming in the Unix/Linux environment using Python, Java, C/C++, or Julia; must have experience with algorithms, numerical techniques, and computational methods, specifically for uncertainty
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uncertainty quantification into scientific machine learning workflows and optimize the design of computational (ABM) and wet-lab experiments. • Collaborate with mathematical modelers and experimentalists in
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run