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Field
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a multidisciplinary research team focused on developing energy-efficient and fault-tolerant AI systems that can operate reliably in the radiation-rich environment of space. The project integrates
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and sets up experiments in hybrid research environment. 2. Researches artificial intelligence/machine learning algorithms, database design, deep learning, big data, and cloud computing. 3. Publishes
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occupant harm from exposure to indoor bioaerosols. Key Responsibilities Responsibilities include, but are not limited to: Developing and analyzing new HVAC control algorithms to balance energy efficiency and
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-based simulation model for assessing future mobility technologies in the Greater Copenhagen region. Explore the development of machine-learning based scenario discovery for future mobility policy design
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 3 months ago
and accurate orbit determination and hazard assessment methods. Research will center on: (1) developing new observation weighting schemes that exploit the expanded metadata available in the Astrometry
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initiatives towards the development of new environmentally friendly products, cleaner and more sustainable manufacturing and farming processes, new medical treatments, and richer biodiversity and ecosystems. In
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learning algorithms into professional software with an intuitive user interface, incorporating feedback from CHWs through iterative design and evaluation cycles. The selected candidate will be part of a
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research in neuro-symbolic AI, with a focus on using generative AI and prompt engineering as a method to engineer knowledge graphs one can trust. This includes the design of algorithms and architectures, but
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University, to begin as early as July 1, 2025. Topics include the experimental quantum simulation of chemical and condensed-matter systems using 1D and 2D ion arrays, and the development and optimization
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. The HEXAPIC project aims to develop a novel high-performance Particle-In-Cell (PIC) code for plasma physics simulations, leveraging the capabilities of exascale computing systems. By optimizing PIC algorithms