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Quantum AI Research Scientist

Nexus Future Labs
Austin
Estimated Salary
USD 185.000 – USD 275.000
Live Update
19 Mei 2026
Deadline
19 Mei 2027

Job Description

Join Nexus Future Labs at the forefront of technological evolution as we pioneer the next generation of AI systems. We're seeking a visionary Quantum AI Research Scientist to architect hybrid quantum-classical algorithms that will redefine machine learning by 2026. You'll collaborate with Nobel laureates and industry disruptors in our state-of-the-art Austin facility, where cutting-edge research meets commercial application.

Why Nexus? We offer patent ownership opportunities, unlimited research budgets, and equity in breakthrough technologies. Our Austin campus features a quantum computing lab, neuro-interfaces lab, and dedicated AI ethics council – all powered by 100% renewable energy.

Responsibilities

  • Design and implement quantum neural network architectures for 2026-era AI systems
  • Lead cross-functional teams in developing hybrid quantum-classical ML pipelines
  • Publish breakthrough research in top-tier journals (Nature, Science, etc.)
  • Secure $5M+ in quantum computing research grants
  • Develop ethical frameworks for quantum AI deployment
  • Collaborate with hardware teams to optimize quantum-classical interfaces
  • Mentor postdoctoral researchers in quantum machine learning

Qualifications

  • PhD in Quantum Computing, Physics, or Computer Science with 3+ years postdoc experience
  • Published research in quantum machine learning or quantum algorithms
  • Expertise in quantum programming languages (Q#, Qiskit, Cirq)
  • Proficiency in quantum error correction and fault-tolerant design
  • Deep understanding of quantum supremacy benchmarks
  • Experience with high-performance computing architectures
  • Strong background in computational complexity theory
  • Portfolio demonstrating quantum AI implementations

Required Skills

Quantum Computing Quantum Algorithms Machine Learning Quantum Programming Qiskit Cirq Python High-Performance Computing Quantum Error Correction

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