Job Description
Join Nexus Labs at the forefront of technological innovation as we pioneer the quantum revolution of 2026. We're seeking a visionary Quantum Computing Research Scientist to architect the next generation of computational paradigms that will redefine industries. In this cutting-edge role, you'll collaborate with Nobel laureates and industry pioneers to solve humanity's most complex challenges—from drug discovery to climate modeling. Our state-of-the-art lab in San Francisco offers unparalleled resources including quantum annealers, superconducting processors, and exclusive industry partnerships. This isn't just a job; it's your chance to shape the digital future.
We offer competitive equity packages, flexible hybrid work arrangements, and comprehensive benefits including wellness stipends and sabbatical programs. Our culture values intellectual curiosity above all else—here, failure is redefined as experimental data.
Responsibilities
- Design and implement novel quantum algorithms for practical applications in cryptography and optimization
- Lead experimental research on quantum hardware systems including superconducting qubits and topological processors
- Develop hybrid quantum-classical machine learning frameworks for predictive modeling
- Collaborate with cross-functional teams to integrate quantum solutions into enterprise systems
- Author breakthrough research papers for premier journals and conferences
- Secure $1M+ in research grants and patents for quantum innovations
- Mentor PhD candidates and junior researchers in quantum methodologies
Qualifications
- PhD in Quantum Physics, Computer Science, or related field with 3+ years industry experience
- Expertise in quantum gate operations, error correction protocols, and decoherence mitigation
- Proficiency with quantum programming frameworks (Qiskit, Cirq, Q#) and simulation tools
- Published research in Nature/Science journals or equivalent top-tier publications
- Demonstrated experience with quantum hardware platforms (IBM Quantum, Rigetti, IonQ)
- Strong background in linear algebra, complex analysis, and statistical mechanics
- Track record of translating theoretical concepts into scalable implementations