Job Description
Join Nexus Labs at the forefront of quantum innovation as we pioneer breakthroughs for the 2026 technology revolution. We seek a visionary Research Lead to drive our next-gen quantum computing initiatives, transforming theoretical possibilities into scalable solutions that will redefine industries.
As a key architect of our 2026 quantum roadmap, you'll collaborate with Nobel laureates, government agencies, and Fortune 500 partners to develop fault-tolerant quantum systems. Our Austin hub offers unparalleled resourcesâincluding a 128-qubit quantum processor and dedicated cryogenic labsâenabling you to push boundaries where others hesitate.
This role represents a unique opportunity to shape humanity's technological trajectory during the most transformative decade since the digital revolution. Compensation includes equity in our pre-IPO quantum startup and access to our exclusive 'Future Innovators' executive retreat series.
Responsibilities
- Lead research initiatives in quantum error correction and algorithm optimization for 2026 deployment targets
- Design scalable quantum architectures compatible with existing cloud infrastructure
- Secure $5M+ in government/industry grants for quantum security applications
- Publish 3+ breakthrough papers in Nature/Science journals annually
- Mentor cross-disciplinary teams of physicists, cryptographers, and ML specialists
- Develop quantum-safe cryptographic protocols for critical infrastructure
- Present findings at Davos, IEEE Quantum Week, and exclusive industry summits
Qualifications
- PhD in Quantum Computing, Physics, or Computational Theory with 8+ years industry experience
- Published research in top-tier quantum journals with 50+ citations
- Expertise in quantum annealing, superconducting qubits, and topological quantum computing
- Proven track record of securing $10M+ in research funding
- Proficiency in Qiskit, Cirq, and quantum circuit optimization frameworks
- Experience with cryogenic engineering and quantum control systems
- Deep understanding of quantum machine learning and NISQ-era limitations