Job Description
Join Nexus Quantum Labs at the forefront of technological evolution as we pioneer quantum computing breakthroughs for 2026 and beyond. We seek visionary Research Scientists to develop next-gen quantum algorithms and applications that will redefine industries. Our state-of-the-art facility in San Francisco offers unparalleled resources and a collaborative environment where innovation thrives.
This role offers the unique opportunity to work on cutting-edge quantum hardware, error correction, and hybrid quantum-classical systems. You'll collaborate with Nobel laureates and industry pioneers while contributing to projects that will shape humanity's technological future.
Responsibilities
- Design and implement novel quantum algorithms for optimization, cryptography, and machine learning applications
- Develop quantum error correction protocols to enhance qubit stability in 2026-era systems
- Lead research on quantum-classical hybrid computing architectures for real-world deployment
- Collaborate with hardware teams to co-design quantum processors with 1000+ qubit capabilities
- Publish breakthrough research in leading journals and present at international quantum conferences
- Secure external funding through NSF and DARPA proposals for quantum computing initiatives
- Mentor junior researchers and cross-functional teams in quantum principles
Qualifications
- PhD in Quantum Computing, Physics, Computer Science, or related field with 3+ years postdoctoral experience
- Proven expertise in quantum algorithm design and quantum circuit optimization
- Deep understanding of quantum error correction codes and fault-tolerant architectures
- Proficiency in quantum programming languages (Q#, Qiskit, Cirq) and high-performance computing
- Publication record in Nature/Science or equivalent-tier quantum computing journals
- Experience with quantum hardware platforms (superconducting, trapped ions, photonic)
- Demonstrated ability to secure competitive research grants and funding
- Strong background in machine learning and classical HPC systems integration