Job Description
Join NexusLabs at the forefront of technological evolution as we pioneer breakthroughs that will define 2026 and beyond. We seek a visionary Quantum Computing Research Scientist to architect next-generation computational paradigms. You'll collaborate with Nobel laureates and industry disruptors to solve humanity's most complex challenges—from climate modeling to drug discovery. Our state-of-the-art quantum lab in San Francisco offers unparalleled resources to transform theoretical concepts into real-world applications. If you thrive at the intersection of physics, computer science, and exponential innovation, this is your moment to shape the future.
Responsibilities
- Design and implement novel quantum algorithms for practical applications in AI, cryptography, and materials science
- Lead multi-disciplinary teams in developing quantum error correction protocols for fault-tolerant systems
- Drive research initiatives in quantum machine learning and hybrid quantum-classical architectures
- Collaborate with hardware engineers to optimize quantum processor performance and scalability
- Publish groundbreaking research in top-tier journals and present findings at global tech conferences
- Develop strategic roadmaps for quantum adoption across healthcare, finance, and energy sectors
- Secure and manage research partnerships with academic institutions and government agencies
Qualifications
- PhD in Quantum Physics, Computer Science, or related field with 5+ years of quantum research experience
- Proven expertise in quantum programming languages (Q#, Qiskit, Cirq) and quantum circuit design
- Published research in quantum algorithms or quantum error correction (minimum 3 peer-reviewed papers)
- Deep understanding of quantum hardware architectures (superconducting, trapped-ion, photonic)
- Experience with cloud quantum platforms (IBM Quantum, AWS Braket, Azure Quantum)
- Strong background in high-performance computing and parallel processing frameworks
- Demonstrated ability to translate theoretical quantum concepts into scalable implementations