Job Description
Join Nexus Labs at the forefront of technological innovation as we pioneer quantum computing solutions for 2026 and beyond. We're seeking a visionary Quantum Computing Research Scientist to develop next-generation algorithms and hardware architectures that will redefine computational boundaries. You'll collaborate with Nobel laureates and industry disruptors in our state-of-the-art Austin facility, contributing to projects that could revolutionize cryptography, AI, and materials science.
What You'll Achieve: Design and implement quantum algorithms for complex optimization problems; pioneer error-correction techniques for scalable quantum systems; publish groundbreaking research in top-tier journals; mentor the next generation of quantum pioneers.
Why Nexus Labs? We offer competitive equity packages, unlimited R&D budgets, and direct access to our quantum annealing hardware. Our Austin campus features a 500-qubit quantum processor and dedicated innovation labs.
Responsibilities
- Develop novel quantum algorithms for practical applications in finance, logistics, and drug discovery
- Design and test quantum error-correction protocols to achieve fault-tolerant computation
- Collaborate with hardware engineers to optimize quantum processor architectures
- Lead cross-functional projects integrating quantum solutions with classical AI systems
- Publish peer-reviewed research and present findings at international conferences
- Mentor junior researchers and contribute to quantum computing education initiatives
Qualifications
- PhD in Physics, Computer Science, or related field with quantum computing specialization
- 3+ years of hands-on experience with quantum programming languages (Qiskit, Cirq, or Quipper)
- Published research in quantum algorithm design or quantum error correction
- Proficiency in quantum circuit simulation and optimization techniques
- Demonstrated ability to translate theoretical concepts into practical implementations
- Experience with high-performance computing environments and parallel processing
- Strong background in linear algebra, probability theory, and computational complexity