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Quantum AI Research Scientist

Nexus Labs
Austin
Estimated Salary
USD 180.000 – USD 280.000
New
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

Join Nexus Labs at the cutting edge of technological evolution. We're seeking a visionary Quantum AI Research Scientist to architect the next generation of hybrid quantum-AI systems that will redefine computing by 2026. This role sits at the intersection of quantum mechanics, machine learning, and theoretical physics, pushing the boundaries of what's possible in computational intelligence. You'll work in our state-of-the-art Austin R&D facility, collaborating with Nobel laureates and industry pioneers to develop breakthrough algorithms that solve previously intractable problems.

Responsibilities

  • Design and implement novel quantum machine learning algorithms for 2026-era applications
  • Lead research in quantum neural networks and hybrid quantum-classical computing frameworks
  • Develop error-correction protocols for practical quantum AI deployment at scale
  • Collaborate with hardware teams to co-design quantum processors optimized for AI workloads
  • Publish groundbreaking research in top-tier journals and conferences
  • Drive patent creation for proprietary quantum AI methodologies
  • Mentor cross-disciplinary teams of physicists, computer scientists, and engineers

Qualifications

  • PhD in Quantum Computing, Machine Learning, or Theoretical Physics
  • 3+ years of experience in quantum algorithm development or quantum machine learning
  • Proficiency in Python, Qiskit, Cirq, and quantum circuit optimization
  • Published research in quantum computing or AI at venues like Nature Quantum or NeurIPS
  • Deep understanding of quantum error correction and fault-tolerant architectures
  • Expertise in at least one classical ML framework (TensorFlow/PyTorch)
  • Strong background in linear algebra, probability theory, and computational complexity

Required Skills

Quantum Computing Machine Learning AI Research Quantum Algorithms Python Qiskit TensorFlow Theoretical Physics

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