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Quantum AI Research Lead - 2026

Nexus Quantum Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Shape the future of human-machine intelligence at Nexus Quantum Labs. As we pioneer the convergence of quantum computing and artificial intelligence by 2026, we seek a visionary Quantum AI Research Lead to architect breakthrough systems that will redefine computational boundaries. Join our Austin-based team where theoretical physics meets practical innovation, and help build the next generation of autonomous quantum neural networks.

Responsibilities

  • Lead quantum AI research initiatives focusing on error-corrected neural networks and hybrid quantum-classical architectures
  • Develop proprietary quantum algorithms for unsupervised learning and optimization problems
  • Collaborate with hardware engineers to design quantum processors optimized for AI workloads
  • Secure multi-million dollar research grants from DARPA, NSF, and industry partners
  • Mentor cross-functional teams of quantum physicists, ML engineers, and domain specialists
  • Publish findings in Nature/Science journals and lead industry conferences
  • Establish ethical frameworks for quantum AI deployment in critical infrastructure

Qualifications

  • PhD in Quantum Computing, Theoretical Physics, or Machine Learning with 5+ years industry research experience
  • Published work in top-tier journals on quantum machine learning or quantum algorithms
  • Expertise in quantum programming frameworks (Qiskit, Cirq, PennyLane) and ML libraries (PyTorch, TensorFlow)
  • Proven track record of securing government research grants ($1M+)
  • Deep understanding of quantum error correction and fault-tolerant systems
  • Experience mentoring postdoctoral researchers and leading international teams
  • Strong background in computational complexity theory and quantum information theory

Required Skills

Quantum Computing Artificial Intelligence Machine Learning Quantum Algorithms Research Leadership Grant Writing Error Correction Neural Networks

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