Job Description
Join Nexus Labs at the forefront of the 2026 technological revolution. We're pioneering quantum computing solutions to solve humanity's most complex challenges. As a Quantum Computing Research Scientist, you'll architect next-gen algorithms and push the boundaries of computational science in our state-of-the-art San Francisco facility. Collaborate with Nobel laureates and industry disruptors to transform theoretical physics into practical applications that will redefine industries.
Our team operates at the intersection of quantum mechanics, artificial intelligence, and materials science. You'll leverage our $50M quantum infrastructure to develop error-corrected qubits, optimize quantum machine learning models, and pioneer new encryption protocols. This role offers unparalleled opportunities to publish in Nature/Science and commercialize breakthrough innovations.
Responsibilities
- Design and implement quantum algorithms for optimization, simulation, and machine learning applications
- Lead cross-functional teams in developing fault-tolerant quantum computing architectures
- Collaborate with materials scientists to engineer novel qubit technologies
- Develop quantum error correction protocols for industrial-scale quantum processors
- Translate theoretical quantum physics models into executable code on quantum simulators
- Secure research funding through NSF/NIH grants and industry partnerships
- Mentor junior researchers and publish breakthrough findings in top-tier journals
Qualifications
- PhD in Quantum Physics, Computer Science, or related field with 3+ years research experience
- Expertise in quantum programming languages (Qiskit, Cirq, Q#) and quantum circuit design
- Proficiency in Python/C++ with deep understanding of quantum algorithms (Shor's, Grover's, VQE)
- Publication record in quantum computing or quantum information theory
- Experience with quantum hardware platforms (IBM Quantum, Rigetti, IonQ)
- Demonstrated ability to secure research funding or lead industrial R&D projects
- Strong background in linear algebra, probability theory, and computational complexity