Job Description
Join Nexus Labs at the forefront of quantum-AI convergence to redefine computational boundaries in 2026. We seek a pioneering Research Scientist to develop next-gen quantum neural networks and hybrid quantum-classical systems. This role offers unparalleled access to our quantum annealing infrastructure and collaborative partnerships with leading universities. Shape the future of technology while working in our state-of-the-art San Francisco facility.
Why Nexus Labs? We offer competitive equity packages, flexible hybrid work arrangements, and dedicated R&D funding for experimental projects. Our cross-functional teams include Nobel laureates and Turing Award winners.
Responsibilities
- Design and implement quantum machine learning algorithms for 2026-era computational challenges
- Lead research on quantum neural network architectures and error mitigation protocols
- Collaborate with hardware teams to optimize quantum-classical hybrid systems
- Develop novel approaches to quantum data compression and pattern recognition
- Publish breakthrough research in Nature/Science journals and present at IEEE Quantum Week
- Mentor junior researchers and contribute to quantum-AI curriculum development
- Secure external funding through NSF and DARPA quantum initiatives
Qualifications
- PhD in Quantum Physics, Computer Science, or related field (2020-2024 graduates encouraged)
- Expertise in quantum algorithms, QML frameworks (Qiskit, PennyLane), and tensor networks
- Published research in quantum computing or machine learning (arXiv/peer-reviewed)
- Proficiency in Python/C++ with quantum simulation experience (Q#, Cirq)
- Demonstrated ability to collaborate across physics/AI disciplines
- Strong background in high-performance computing and parallel processing
- Experience with cloud quantum platforms (IBM Quantum, Amazon Braket)