Job Description
Join Nexus Quantum Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. We seek an exceptional Research Scientist to develop next-generation quantum algorithms and hardware prototypes in our state-of-the-art San Francisco facility. This role offers unparalleled opportunity to shape the future of computational science while collaborating with Nobel laureates and industry disruptors.
Our team operates at the intersection of physics, computer science, and AI, pushing boundaries in quantum supremacy, error correction, and practical quantum applications. You'll contribute to breakthrough projects with global impact while enjoying competitive compensation, flexible work arrangements, and comprehensive benefits including equity participation.
Responsibilities
- Design and implement novel quantum algorithms for optimization and machine learning challenges
- Lead experimental validation of quantum hardware prototypes in cryogenic environments
- Collaborate with cross-functional teams to develop quantum-classical hybrid computing frameworks
- Publish peer-reviewed research in top-tier journals and present at international conferences
- Secure external research funding through NSF, DoE, and industry partnerships
- Mentor junior researchers and drive innovation in quantum error mitigation techniques
- Contribute to patent development for proprietary quantum computing methodologies
Qualifications
- PhD in Quantum Computing, Physics, Computer Science, or related field (or equivalent experience)
- 3+ years hands-on experience with quantum programming languages (Q#, Qiskit, Cirq)
- Deep understanding of quantum error correction and fault-tolerant architectures
- Published research in quantum algorithms or quantum information theory
- Proficiency with high-performance computing and parallel processing frameworks
- Experience with cryogenic quantum systems or superconducting qubits preferred
- Demonstrated ability to translate theoretical concepts into practical implementations
- Strong analytical skills with attention to experimental rigor and reproducibility