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. The project’s overarching goal is the development of digital quantum algorithms for the simulation of non-abelian lattice gauge theories. We are looking for highly motivated individuals, with the desire
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. The Postdoctoral Associate will apply his/her technical skills toward development and implementation of machine learning, computer vision, and other algorithms for analysis of medical images and prognostication as
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design, development, and validation of material, control systems, and algorithms for next-generation soft haptic actuators and experiences. Note that the research involves significant interactions with
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 1 hour 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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, and maintaining software systems to support these research projects. This includes building data pipelines, developing algorithms, and ensuring that data is stored efficiently and is accessible to all
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Duties Job Duty Category Research Duty/Responsibility Develop and apply knowledge guided machine learning algorithms Evaluate the machine learning models with observational data at site to regional scales
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on developing new cement formulations and characterization techniques. For algorithms and software there will also be the opportunity to work with the team behind the Core Imaging Library (CIL) and contribute
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. This may involve studying how such systems operate in practice, exploring their social and policy impact, or developing technical or regulatory mechanisms that support transparency, oversight, and
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reaction evolution mechanisms for magnesium-based binders, leveraging state-of-the-art experimentation and numerical modelling tools. This position is part of the prestigious Villum Synergy project
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interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific computing and machine learning. The research will emphasize both theoretical