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. The research involves the development of machine learning algorithms and MR pulse sequences for next-generation computational MRI. The research will be conducted at the Electrical and Computer Engineering and
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management system for the e-vessel microgrid for coordinated control of multiple energy sources considering cost, carbon, and operation constraints. Operate the simulated electrical model on a real-time system
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Laboratoire National de Métrologie et d'Essais - LNE | Paris 15, le de France | France | 3 months ago
on the primary data. They are often captured from multiple scans made from different locations to unspecified surface locations. This introduces novel sources of uncertainty while potentially reducing the impact
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environment such as Matlab/Simulink. Design and develop an intelligent energy management system for the e-vessel microgrid for coordinated control of multiple energy sources considering cost, carbon, and
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University of California, San Francisco | San Francisco, California | United States | about 16 hours ago
, Jupyter, Hadoop, Spark, Hiv Experience analyzing data on the order of tens of billions of records. Fundamental knowledge of computer science, architectures and algorithmic optimization Experience with
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work across disciplines. The candidate will be attached to both FORM (hosted by the Department of Mathematics and Computer Science) and DIAS and should be prepared to engage in multiple and diverse
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quantum information, develop techniques for quantum control and measurement, build quantum computing hardware and software, and explore novel applications. Our main interest is to propose quantum algorithms
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, the ML Engineer hired for this position will work with Benjamin Gyori at Khoury College and Ayan Paul at EAI and is expected to develop AI algorithms for LLM based RAG systems, work with graduate students
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seeking a motivated individual to support and potentially lead research and development tasks relating to data science, machine learning, and algorithmic development related to RF networks. This may include
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learning and artificial intelligence, data-driven methods in scientific computing, discrete and combinatorial algorithms, and high-performance computing and large-scale algorithms. Preferred Qualifications