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Information Technology 🏢 Full Time ⭐️ Verified

2026 Quantum AI Researcher

Nexus Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
27 Mei 2026
Deadline
27 Mei 2027

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer quantum-AI integration for 2026's next-generation computing paradigm. We seek visionary researchers to develop breakthrough algorithms that will redefine machine learning and computational boundaries. Our state-of-the-art facility offers unparalleled resources for collaborative innovation in a dynamic, cross-disciplinary environment. This role represents a rare opportunity to shape the future of intelligent systems while working alongside Nobel-caliber scientists and industry disruptors.

Responsibilities

  • Design and implement quantum machine learning algorithms for 2026-era computing architectures
  • Lead cross-functional R&D initiatives in quantum neural networks and hybrid AI systems
  • Develop novel error-correction protocols for scalable quantum processors
  • Collaborate with hardware teams to optimize quantum-AI co-design solutions
  • Author breakthrough research papers for top-tier scientific journals and conferences
  • Secure federal and private funding for cutting-edge quantum-AI projects
  • Mentor junior researchers in quantum computing best practices

Qualifications

  • PhD in Quantum Computing, Theoretical Physics, or Computer Science
  • 5+ years of experience in quantum algorithm development
  • Published research in Nature/Science or equivalent tier journals
  • Proficiency in Qiskit, Cirq, or equivalent quantum programming frameworks
  • Expertise in tensor networks and quantum machine learning
  • Demonstrated ability to secure competitive research grants
  • Experience with high-performance computing clusters (HPC)
  • Strong background in topological quantum error correction

Required Skills

Quantum Computing Machine Learning Qiskit Cirq Quantum Machine Learning Quantum Error Correction Research AI Theoretical Physics HPC Tensor Networks

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