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Field
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, research, and develop autonomy algorithms that use sonar data operating in complex environments to avoid obstacles, aid multi-agent decision making and dynamically replan current tasking and sorties. Design
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of developing innovative, principled, and insightful leaders who change lives, change organizations, and change the world. The Data, Analytics, and Research Computing team (DARC) of the Stanford Graduate School
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. The incumbent will develop and implement algorithms on existing data warehouse records and may nominate new external data sources to be ingested to the data warehouse to strengthen analyses. Analyses will address
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. The position is part of a small team that works on the development and optimization of algorithms for these problems, as well as proofs on theoretical complexity bounds. Common tasks include: Developing ideas
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sequencing and imaging data to facilitate the paper figures of lab members. Candidate will train on the labâ™s fundamental algorithms and run them in a collaborative manner with other team members to generate
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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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provide insights into comparative physiology across different species. Of particular interest is the modeling of transport networks across multiple scales, including their function, development and
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an active interest in contributing to our undergraduate game development program. Finally, we are looking for candidates focused on algorithmic theory with an emphasis on improving and expanding
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researcher in algorithmic game theory and/or online learning, working with Prof. Celli at BIDSA and the Department of Computing Sciences. The project studies how multiple machine learning algorithms interact
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Support for testing, data analysis, and data display Contribute to the research and development of unique algorithmic solutions for a wide array of sponsor requirements, with a focus on machine learning and