Sort by
Refine Your Search
-
Employer
-
Field
-
) Quantum Error Correction and Fault-Tolerance: Codes and decoders tailored to biased-noise qubits Code surgery compilation Bosonic codes Statistical Mechanics and Non-Equilibrium Many-Body Physics of Error
-
, etc. - ML-augmented numerical method development. - High-performance computing (HPC). - Quantum algorithm design. - Error correction or error mitigation. City
-
Computer Engineering (ECE) is accepting applications for a Postdoctoral Research Associate. The successful candidate will conduct cutting-edge research in quantum error correction and fault-tolerant quantum
-
National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 20 hours ago
or X-ray beamline facilities preferred. Strong analytical skills including multi-system data integration, point spread function analysis, optical modeling, and error analysis. Excellent communication
-
frameworks such as Qiskit, CUDA-Q, PennyLane, Cirq, or equivalent platforms, and knowledge of quantum algorithms, quantum error correction, fault-tolerant computing, or quantum resource estimation. Experience
-
). - Quantum algorithm design. - Error correction or error mitigation. Certifications/Licenses Required Knowledge, Skills, and Abilities Strong background in quantum chemistry, computational physics
-
of Rheumatology/Immunology at WashU. The Schmitt Lab studies immune dysregulation in inborn errors of immunity. We are specifically interested in investigating the mechanisms leading to T and B cell dysregulation
-
at WashU. The Schmitt Lab studies immune dysregulation in inborn errors of immunity. We are specifically interested in investigating the mechanisms leading to T and B cell dysregulation. In complementary
-
in areas related to quantum information theory, quantum error correction, and machine learning. The position will start in fall 2026 and will be for two years, with a possible 1-year extension pending
-
Genome Curation Assistant (Jarvis ): an AI system that combines modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting