Job Description
Join Nexus Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking a visionary Quantum Computing Research Scientist to develop next-gen algorithms and architectures that will redefine computational boundaries. This role offers unparalleled opportunities to collaborate with Nobel laureates and industry disruptors in our state-of-the-art Austin innovation hub.
What you'll achieve:
- Design and implement quantum algorithms solving previously intractable problems in cryptography, AI, and materials science
- Lead breakthrough research in quantum error correction and fault-tolerant systems
- Drive the development of hybrid quantum-classical computing frameworks
- Shape industry standards through peer-reviewed publications and conference presentations
- Mentor the next generation of quantum computing talent
Responsibilities
- Develop novel quantum algorithms for optimization and simulation challenges
- Architect scalable quantum computing systems with fault-tolerant designs
- Collaborate with AI teams to integrate quantum-enhanced machine learning models
- Lead experimental validation of quantum protocols on superconducting and photonic platforms
- Secure intellectual property through patent development
- Present research findings at premier conferences like Q2B and IEEE Quantum Week
- Partner with industry leaders to translate theoretical breakthroughs into commercial applications
Qualifications
- PhD in Quantum Computing, Physics, or Computer Science with 3+ years industry experience
- Expertise in quantum circuit design and quantum error correction techniques
- Proficiency in quantum programming languages (Qiskit, Cirq, Q#)
- Published research in top-tier quantum computing journals or conferences
- Experience with quantum hardware platforms (IBM Q, Rigetti, IonQ)
- Demonstrated ability to secure competitive research grants
- Deep understanding of quantum information theory and complexity classes
- Track record of translating quantum theory into practical applications