Job Description
Join Nexus Labs at the forefront of 2026's quantum-AI convergence. We're pioneering next-generation computational frameworks that will redefine industries by 2026. As a Quantum AI Research Scientist, you'll architect hybrid quantum-neural systems to solve previously intractable problems in climate modeling, drug discovery, and materials science.
Our Austin-based innovation hub offers unparalleled resources: access to 512-qubit quantum processors, petascale GPU clusters, and cross-disciplinary collaboration with Nobel laureates. We provide comprehensive benefits including equity, relocation stipends, and flexible R&D time for moonshot projects.
Responsibilities
- Design and implement quantum machine learning algorithms for 2026-era applications
- Lead cross-functional teams in developing hybrid quantum-classical computing frameworks
- Publish breakthrough research in top-tier journals/conferences (Nature, NeurIPS, QIP)
- Translate theoretical models into scalable production systems with 99.99% reliability
- Secure $5M+ in federal/industry grants for 2026 quantum-AI initiatives
- Mentor PhD researchers on quantum neural network optimization techniques
Qualifications
- PhD in Quantum Computing, Machine Learning, or Computational Physics
- 5+ years experience with quantum programming (Qiskit, Cirq) and deep learning frameworks
- Published work in quantum machine learning or top-tier AI conferences
- Expertise in error correction for NISQ-era quantum processors
- Proficiency in high-performance computing environments (HPC, GPU clusters)
- Track record of securing competitive research funding
- Strong background in tensor networks or quantum circuit optimization