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Quantum AI Research Scientist

Nexus Quantum Labs
Austin
Estimated Salary
USD 180.000 – USD 280.000
New
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Join Nexus Quantum Labs at the forefront of technological evolution. We're pioneering quantum-AI fusion systems that will redefine computing by 2026. As a Quantum AI Research Scientist, you'll architect next-generation algorithms leveraging quantum entanglement and neural networks to solve previously unsolvable challenges in cryptography, materials science, and autonomous systems.

Our Austin campus features a state-of-the-art quantum lab and AI supercomputing cluster. You'll collaborate with Nobel laureates and industry disruptors in an environment where theoretical physics meets practical application. We offer competitive equity packages and dedicated R&D funding for breakthrough projects.

Responsibilities

  • Design and implement quantum machine learning algorithms for 2026-era computational challenges
  • Lead cross-functional teams in developing hybrid quantum-classical computing architectures
  • Author peer-reviewed publications on quantum-AI convergence and publish in Nature/Science journals
  • Secure patents for novel quantum encryption methods and AI optimization techniques
  • Mentor PhD researchers and drive innovation in quantum neural networks
  • Partner with government agencies on national quantum security initiatives

Qualifications

  • PhD in Quantum Computing, Machine Learning, or Theoretical Physics (post-doc preferred)
  • 5+ years experience with quantum algorithms (Q#, Qiskit, or Cirq)
  • Published research in quantum machine learning or quantum cryptography
  • Expertise in tensor networks and quantum circuit optimization
  • Proficiency in high-performance computing environments (HPC/AI clusters)
  • Strong background in cryptography and information theory
  • Demonstrated ability to secure government or corporate research grants

Required Skills

Quantum Computing Machine Learning Theoretical Physics Quantum Algorithms Cryptography High-Performance Computing Neural Networks Research Austin Tech

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