Job Description
Shape the future of technology with Nexus Quantum Solutions, a pioneer in quantum computing innovation. We seek a visionary Quantum Computing Research Scientist to join our elite team in San Francisco. This role offers an unparalleled opportunity to work on next-generation quantum algorithms, hardware integration, and real-world applications that will redefine computing by 2026.
You'll collaborate with Nobel laureates and industry disruptors in our state-of-the-art facility, leveraging resources from our partnership with leading quantum hardware providers. We offer competitive equity packages, unlimited learning stipends, and the chance to publish groundbreaking research in top-tier journals.
Join us to solve humanity's most complex challenges—from drug discovery to climate modeling—and accelerate the quantum revolution.
Responsibilities
- Design and implement novel quantum algorithms for practical applications in cryptography, optimization, and machine learning
- Lead experimental validation of quantum circuits on superconducting and photonic platforms
- Develop error-correction protocols to achieve fault-tolerant quantum computation
- Collaborate with hardware teams to co-design quantum processors for specific workloads
- Author peer-reviewed publications and patents in quantum computing
- Mentor junior researchers and contribute to open-source quantum frameworks
- Drive roadmap for 2026 quantum computing deliverables and industry partnerships
Qualifications
- PhD in Quantum Physics, Computer Science, or related field with 3+ years of quantum research experience
- Expertise in quantum circuit design and quantum error correction techniques
- Proficiency in quantum programming languages (Qiskit, Cirq, Q#) and simulation frameworks
- Published research in quantum computing or quantum information theory
- Experience with quantum hardware platforms (IBM Quantum, Rigetti, IonQ)
- Strong background in linear algebra, probability, and statistical mechanics
- Track record of translating theoretical concepts into practical implementations