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Field
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) Research Experience: Relevant research experience in related problem domains, or research experience in scheduling, routing, and multi-agent pathfinding (MAPF) algorithms - Experience across multiple areas
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multi-agent pathfinding (MAPF) algorithms - Experience across multiple areas is a strong plus; Experience developing ML-based optimization approaches is a strong plus; A strong publication track record is
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-series modeling, and clustering algorithms. The candidate is expected to lead an effort to prepare generalized ML techniques for data quality monitoring for tasks across multiple HEP experiments
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will be responsible for programming and maintaining gait exoskeleton systems, developing and implementing real-time control algorithms in C/C++, Python, and Simulink, as well as integrating feedback from
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research subject for this position is development of distributed processing strategies and algorithms for Large Intelligent Surfaces, including both joint baseband processing and synchronization across
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of AI for the integration of multimodal healthcare data specifically incorporating patient preferences. This includes investigating new methods but also designing and benchmarking integration algorithms
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designing and benchmarking integration algorithms. The position is situated in the Intelligent Data Engineering Lab and will be supervised by Dr. Jan-Christoph Kalo and Prof. Paul Groth. What you will do
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 12 hours ago
and implementing real-time control algorithms in C/C++, Python, and Simulink, as well as integrating feedback from wearable sensors (e.g., accelerometry, electromyography) and ultrasound imaging
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 35 minutes ago
supporting multiple probes simultaneously. Swarms also provide the usual benefits of multi-element array reception, namely robustness to single point failures and transmit/receive diversity. The downside
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(MERCE). The main objective is to develop safe planning and reinforcement learning algorithms with various degrees of confidence for variants of Markov decision processes. More precisely, we will develop