Job Description
Join Nexus Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. We seek a visionary Quantum Computing Research Scientist to develop breakthrough algorithms and architectures that will redefine computational boundaries. This role offers unparalleled opportunity to shape the next generation of technology while collaborating with Nobel laureates and industry pioneers.
Our state-of-the-art San Francisco campus features quantum annealing labs, AI-driven research platforms, and a collaborative workspace designed for innovation. We provide comprehensive benefits including equity grants, wellness stipends, and flexible work arrangements. Be part of the team that's solving humanity's most complex challenges through quantum supremacy.
Responsibilities
- Design and implement novel quantum algorithms for optimization, cryptography, and machine learning applications
- Lead quantum hardware-software co-design projects in partnership with quantum computing manufacturers
- Develop error mitigation techniques to achieve practical quantum advantage in real-world scenarios
- Publish groundbreaking research in top-tier journals and present at international quantum conferences
- Mentor junior researchers and foster cross-functional collaboration between physics, computer science, and engineering teams
- Secure external funding through NSF grants and industry partnerships for quantum research initiatives
Qualifications
- PhD in Quantum Computing, Physics, Computer Science, or related field with 5+ years research experience
- Expertise in quantum programming languages (Qiskit, Cirq, Q#) and quantum circuit optimization
- Published record in quantum algorithms or quantum error correction in peer-reviewed journals
- Proficiency with high-performance computing environments and quantum simulation frameworks
- Demonstrated ability to translate theoretical quantum concepts into practical implementations
- Strong background in linear algebra, quantum mechanics, and computational complexity theory