Job Description
Shape the future of technology at Nexus Labs. We're seeking visionary Quantum Computing Research Leads to pioneer breakthroughs in 2026's most transformative technology. Join our elite team at the intersection of quantum mechanics, AI, and sustainable innovation, where your work will redefine computational boundaries.
About Nexus Labs: A Silicon Valley trailblack in emergent technologies, we're accelerating the quantum revolution with $500M in R&D funding and partnerships with MIT, Stanford, and NASA. Our San Francisco campus features state-of-the-art quantum labs and collaborative innovation spaces.
What you'll impact: Lead research teams in quantum error correction, develop next-gen quantum algorithms, and contribute to our 2026 quantum supremacy roadmap. Your work will directly influence industries from pharmaceuticals to climate modeling.
Responsibilities
- Lead cross-functional quantum research teams developing proprietary algorithms for 2026-era applications
- Design and implement quantum error correction protocols to achieve fault-tolerant computation
- Collaborate with AI specialists to create hybrid quantum-classical machine learning models
- Publish peer-reviewed research in top-tier journals (Nature, Science, Quantum)
- Secure federal and private research grants ($5M+ target annually)
- Mentor PhD researchers and quantum engineering fellows
- Develop quantum-secure encryption protocols for next-gen communications
Qualifications
- PhD in Quantum Physics, Computer Science, or related field (postdoc preferred)
- 5+ years experience with quantum computing hardware (superconducting, ion trap, photonic)
- Publication record in quantum algorithms or error correction
- Expertise in Qiskit, Cirq, or equivalent quantum programming frameworks
- Deep understanding of quantum decoherence and mitigation strategies
- Experience securing DoD/NSF quantum research grants
- Strong background in topological quantum computing or quantum machine learning
- Validated ability to lead technical teams through experimental validation cycles