Job Description
Join Nexus Quantum Labs at the forefront of the 2026 technological revolution. We're pioneering quantum computing solutions that will redefine global industries, and we seek exceptional minds to accelerate our mission. As a Quantum Computing Research Scientist, you'll collaborate with Nobel laureates and industry disruptors in our Austin-based quantum hub. We offer competitive compensation, equity packages, and unparalleled resources to push the boundaries of what's computationally possible.
Our Austin campus features state-of-the-art quantum labs, 24/7 access to supercomputing resources, and a culture where unconventional thinking thrives. You'll work on projects with direct impact on cryptography, drug discovery, and AI optimization—transforming theoretical concepts into real-world applications by 2026.
Responsibilities
- Design and implement novel quantum algorithms for practical 2026-era applications
- Lead cross-functional teams in developing quantum error correction protocols
- Collaborate with hardware engineers to optimize quantum circuit architectures
- Publish breakthrough research in top-tier journals (Nature, Science, etc.)
- Develop quantum machine learning frameworks for next-gen AI systems
- Secure and manage $5M+ research grants from government and private sectors
- Mentor PhD candidates and postdocs in quantum information theory
- Present findings at global quantum computing summits and industry forums
Qualifications
- PhD in Quantum Physics, Computer Science, or Mathematics with 5+ years research experience
- Published work in quantum algorithms or quantum error correction (arXiv/peer-reviewed)
- Expertise in quantum programming frameworks (Qiskit, Cirq, PennyLane)
- Proven track record of securing competitive research grants
- Deep understanding of quantum supremacy challenges and mitigation strategies
- Experience with cryogenic quantum systems and photonic processors
- Strong background in topological quantum computing and fault-tolerant architectures
- Exceptional problem-solving skills with complex multi-variable systems