Job Description
Shape the future of technology as a Quantum Computing Research Scientist at Nexus Quantum Labs. We're pioneering quantum algorithms that will revolutionize cryptography, AI, and materials science by 2026. Join our elite team of physicists and engineers in Austin's innovation corridor, where you'll develop next-gen quantum systems that solve previously impossible computational challenges. Our state-of-the-art lab offers unparalleled resources for breakthrough research in fault-tolerant quantum computing and quantum machine learning.
This role bridges theoretical physics and practical application, requiring both deep scientific expertise and innovative problem-solving. You'll collaborate with Nobel laureates and industry pioneers while contributing to projects that will redefine technological landscapes. We offer competitive compensation, flexible work arrangements, and opportunities to publish groundbreaking research in top-tier journals.
Responsibilities
- Design and implement novel quantum algorithms for optimization, simulation, and machine learning applications
- Develop error-correction protocols to achieve fault-tolerant quantum computation
- Lead experimental validation of quantum circuits on superconducting and photonic platforms
- Collaborate with hardware engineers to optimize quantum processor performance
- Develop quantum machine learning frameworks for predictive modeling and pattern recognition
- Publish research in Nature, Science, and IEEE Quantum journals
- Secure federal and private research grants for quantum computing initiatives
Qualifications
- PhD in Quantum Computing, Physics, or Computer Science with 3+ years of research experience
- Expertise in quantum programming languages (Qiskit, Cirq, Q#) and simulation frameworks
- Published record in quantum error correction or quantum algorithm development
- Proficiency in quantum hardware architectures including superconducting qubits and ion traps
- Experience with high-performance computing environments and parallel processing
- Strong background in linear algebra, probability theory, and computational complexity
- Proven ability to secure research funding through NSF or DoE grants