Job Description
Join Nexus Labs at the forefront of technological evolution as we pioneer quantum-AI hybrid systems for 2026 and beyond. We're seeking visionary researchers to decode the future of computational intelligence through quantum neural networks. This role offers unparalleled access to cutting-edge hardware, collaborative partnerships with global academic institutions, and the opportunity to shape humanity's technological trajectory.
Our state-of-the-art facility in San Francisco's innovation district provides an immersive environment where theoretical physics meets applied machine learning. You'll work alongside Nobel laureates and industry disruptors while contributing to projects that will redefine computing paradigms.
Responsibilities
- Design and implement quantum-AI hybrid algorithms for next-generation neural networks
- Lead experimental validation of quantum computational models using D-Wave and IBM quantum processors
- Develop predictive frameworks for technological convergence points between quantum mechanics and AI
- Collaborate with hardware teams to optimize quantum neural network architectures
- Author breakthrough publications in top-tier journals and present at global conferences
- Mentor junior researchers in emerging quantum machine learning methodologies
Qualifications
- PhD in Quantum Computing, Machine Learning, or Computational Physics (or equivalent research experience)
- Expertise in quantum algorithms (QAOA, VQE, QML frameworks)
- Proficiency in Python/C++ with quantum libraries (Qiskit, Cirq, PennyLane)
- Publication record in Nature/Science or equivalent tier journals
- Demonstrated experience with quantum hardware interfaces
- Strong background in tensor networks and quantum error correction
- Ability to translate complex theoretical concepts into practical implementations