Job Description
Join Nexus Labs at the forefront of technological evolution as we pioneer breakthroughs in quantum computing for 2026. We seek a visionary Quantum Computing Research Scientist to develop next-gen algorithms and hardware solutions that will redefine computational boundaries. You'll collaborate with Nobel laureates in our state-of-the-art Austin facility, leveraging $50M+ in quantum infrastructure to solve humanity's most complex challenges.
Our team operates at the intersection of physics, computer science, and AI innovation. You'll contribute to projects spanning quantum cryptography, error correction, and molecular simulation while mentoring the next generation of quantum pioneers. This role offers unparalleled opportunities to shape the technological landscape of the coming decade.
Responsibilities
- Design and implement novel quantum algorithms for optimization and simulation problems
- Lead experimental validation of quantum hardware prototypes at cryogenic temperatures
- Develop error mitigation techniques for fault-tolerant quantum systems
- Collaborate with cross-functional teams to integrate quantum solutions with classical AI frameworks
- Publish groundbreaking research in top-tier journals and present at international conferences
- Secure $1M+ in research funding through grant proposals and industry partnerships
- Mentor PhD candidates and postdoctoral researchers in quantum computing methodologies
Qualifications
- PhD in Quantum Computing, Physics, or Computer Science with 3+ years of research experience
- Proven expertise in quantum algorithm design (QAOA, VQE, Shor's variants)
- Proficiency with quantum programming frameworks (Qiskit, Cirq, PennyLane)
- Experience with superconducting qubit systems or ion trap technologies
- Strong publication record in quantum information science (arXiv:quant-ph)
- Deep understanding of quantum error correction codes (surface, LDPC, etc.)
- Demonstrated ability to secure competitive research grants (NSF, DOE, DARPA)
- Exceptional problem-solving skills for NP-hard computational challenges