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in classical and quantum error correction, under the direction of Dr. Bane Vasic. More specifically, we are seeking candidates specializing in fault-tolerant error correction, quantum low-density
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. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics for real-time battery health monitoring and fault detection. Collaborate with
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the autonomous event reaction management part of the fault detection, isolation and recovery (FDIR) software. (a)Assessing the performance and fault tolerance of neuromorphic hardware The main objective
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synthetic microorganisms to detect and destroy bacterial and fungal pathogens selectively. SynThera consortium contains ten research groups and is coordinated by Prof. Dr. Kai Papenfort and Prof. Dr. Miriam
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(e.g. in automotive applications) using, for example, vibration and acoustic signals. Research questions include method development for fault detection and isolation, damage estimation systems, including
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continuous-variable quantum computing using 3D cluster states and hybrid (photon number + quadrature) detection. TopQC2X (Innovation Fund Denmark): Experimental primitives for topological quantum computing
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systems including fault detection, diagnosis, and performance improvement methods. Mastery of dynamic reconfiguration approaches. Mastery of power converters. Mastery of software tools including MATLAB
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 5 hours ago
error modeling and encounter clustering (Sentry) Field of Science: Planetary Science Advisors: Steven Chesley steve.chesley@jpl.nasa.gov (818) 354-9615 Applications with citizens from Designated Countries
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creating the fastest algorithms for modeling of entanglement purification circuits; creating the highest performance quantum error detection circuits; developing symbolic computer algebra systems for quantum
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are not limited to superconducting quantum circuits, circuit QED, quantum error correction, microwave quantum optics, variational quantum algorithms, and the application of machine learning to quantum