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Quantum AI Research Scientist

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

Job Description

Join the forefront of technological revolution at Nexus Quantum Labs as we pioneer the next era of computing. We're seeking a visionary Quantum AI Research Scientist to architect breakthrough solutions that will redefine industries by 2026. This role combines quantum mechanics, artificial intelligence, and computational theory to solve previously impossible challenges.

In our state-of-the-art San Francisco facility, you'll collaborate with Nobel laureates and industry pioneers to develop hybrid quantum-AI systems. We offer unparalleled resources, flexible work arrangements, and the opportunity to shape humanity's technological future. Your work will directly impact fields from drug discovery to climate modeling.

Responsibilities

  • Design and implement quantum neural networks for AI acceleration
  • Develop error-correction protocols for fault-tolerant quantum computing
  • Create hybrid quantum-classical algorithms for optimization problems
  • Lead cross-functional R&D projects with quantum physics and AI teams
  • Publish peer-reviewed research in top-tier scientific journals
  • Secure patents for novel quantum-AI methodologies
  • Mentor junior researchers in quantum computing best practices

Qualifications

  • PhD in Quantum Computing, Theoretical Physics, or AI with 5+ years research experience
  • Expertise in quantum algorithms (Shor's, Grover's, VQE) and quantum machine learning
  • Proficiency in quantum programming languages (Q#, Qiskit, Cirq) and Python frameworks
  • Published research in quantum information science or AI
  • Strong background in linear algebra, quantum mechanics, and computational complexity
  • Experience with quantum hardware platforms (IBM Quantum, Rigetti, IonQ)
  • Proven ability to translate theoretical concepts into practical implementations

Required Skills

Quantum Computing Artificial Intelligence Machine Learning Quantum Algorithms Q# Python Theoretical Physics Error Correction

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