Job Description
Join Nexus Quantum Labs at the forefront of technological revolution as we pioneer the next generation of quantum-AI hybrid systems. We're seeking visionary researchers to develop breakthrough algorithms for quantum machine learning applications that will redefine computational capabilities by 2026. Our state-of-the-art facility in San Francisco offers unparalleled resources for exploring quantum supremacy, error correction, and neural-network quantum interfaces. This role includes competitive equity packages, flexible remote work options, and collaboration with Nobel laureates in our multidisciplinary teams. Shape the future of computational intelligence while enjoying California's premier tech ecosystem.
Responsibilities
- Design and implement quantum machine learning algorithms for optimization and pattern recognition
- Lead research on quantum neural network architectures and hybrid quantum-classical models
- Develop error mitigation protocols for near-term quantum processors
- Collaborate with hardware teams to optimize quantum-AI system integration
- Publish high-impact research in leading journals and conferences
- Secure federal and private research funding through grant proposals
- Mentor junior researchers and PhD candidates in quantum computing methodologies
Qualifications
- PhD in Quantum Computing, Physics, Computer Science, or related field
- 3+ years of experience with quantum programming languages (Q#, Qiskit, Cirq)
- Expertise in machine learning frameworks (PyTorch, TensorFlow) and quantum algorithms
- Published research in quantum machine learning or quantum information theory
- Strong mathematical background in linear algebra, probability, and quantum mechanics
- Experience with cloud quantum computing platforms (IBM Quantum, Amazon Braket)
- Demonstrated ability to lead cross-functional technical projects