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domestic, one local). Monitor field instrument performance and troubleshoot issues. Lead efforts to gather, analyze, and interpret H2 and sensor data using findable, accessible, interoperable, and reusable
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, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering, networking, operating systems and security. Job Description We are seeking
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, robustness under varying turbulence, and autonomy for distributed systems. To address this, the group integrates Artificial Intelligence into AO control loops, using deep learning to handle sensor
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characterization and large-scale component testing, including the setup and use of conventional and advanced sensing technologies (e.g., displacement/strain sensors, DIC, fiber-optic sensing). Analyze experimental
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for the High-Luminosity LHC. Our primary responsibility is the integration of double-sided silicon sensors onto mechanical support structures (ladders), including the associated electrical, optical, and cooling
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. Essential Duties and Responsibilities: Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software packages for data
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for: • Contributing to various tasks related to the modeling of lipids and membrane proteins involved in lipid droplet biogenesis. • Developing and implementing the POP-MD algorithm in the OpenMM software
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School of Medicine Established in 1930, Duke University School of Medicine is the youngest of the nation's top medical schools. Ranked sixth among medical schools in the nation, the School takes
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algorithmic graph theory. The purpose of the role is to contribute to the project "Algorithmic meta-classifications for graph containment", working with Professor Matthew Johnson, Dr Barnaby Martin and
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learning, and generative AI Design and implement algorithms for quantum-inspired and quantum-enhanced generative models Investigate theoretical foundations of tensor networks, entanglement, and collapse