Job Description
Join Nexus Future Labs at the frontier of technological innovation. We're seeking a visionary Quantum Computing Research Scientist to architect solutions that will redefine computing paradigms by 2026. In this role, you'll pioneer breakthroughs in quantum algorithms, error correction, and hardware-software co-design while collaborating with Nobel laureates and industry pioneers.
About Nexus Future Labs: We're a preeminent research institute dedicated to accelerating quantum adoption. Our Austin campus houses state-of-the-art cryogenic facilities, 128-qubit processors, and a $200M research endowment. We offer equity grants, unlimited R&D budgets, and flexible remote work options.
Impact: Your work will directly contribute to solving previously impossible problems in drug discovery, climate modeling, and cryptography. We publish 100% of research findings and maintain 100% IP ownership for contributors.
Responsibilities
- Design and implement novel quantum algorithms for optimization problems in computational chemistry and materials science
- Develop quantum error correction protocols to achieve fault-tolerant computation by 2026
- Lead cross-functional teams of physicists, engineers, and software developers to prototype quantum applications
- Author peer-reviewed publications for Nature Physics and IEEE Quantum Journal
- Collaborate with hardware teams to co-design quantum processors with 1000+ qubit capabilities
- Secure $5M+ in DARPA/NSF quantum research grants
- Mentor PhD candidates through our Quantum Fellowship Program
Qualifications
- PhD in Quantum Computing, Theoretical Physics, or Computational Mathematics
- 3+ years of hands-on experience with quantum programming frameworks (Qiskit, Cirq, Q#)
- Published research in top-tier quantum computing conferences (QIP, TQC)
- Expertise in quantum algorithms (Shor's, Grover's, VQE) and complexity theory
- Proficiency in Python/C++ with HPC optimization experience
- Deep understanding of quantum decoherence mitigation techniques
- Track record of translating theoretical models to experimental implementations