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Quantum AI Researcher

Nexus Quantum Labs
San Francisco
Estimated Salary
USD 250.000 – USD 400.000
Live Update
21 Mei 2026
Deadline
21 Mei 2027

Job Description

Shape the future of artificial intelligence at Nexus Quantum Labs! We're seeking visionary Quantum AI Researchers to pioneer breakthroughs at the intersection of quantum computing and machine learning. Join our elite team in San Francisco to develop next-generation algorithms that will redefine technological boundaries by 2026.

Our cutting-edge research lab offers unparalleled resources for exploring quantum neural networks, quantum-resistant cryptography, and hybrid quantum-classical systems. You'll collaborate with Nobel laureates and industry pioneers in an environment that values bold innovation and intellectual curiosity.

Responsibilities

  • Design and implement quantum machine learning algorithms for real-world applications
  • Lead research initiatives in quantum neural networks and quantum-enhanced data processing
  • Develop quantum-resistant cybersecurity protocols for AI systems
  • Collaborate with hardware teams to optimize quantum algorithms on next-gen processors
  • Publish breakthrough research in top-tier scientific journals and conferences
  • Mentor junior researchers and foster cross-disciplinary innovation
  • Secure patents for novel quantum AI methodologies

Qualifications

  • PhD in Quantum Computing, Machine Learning, or Physics with 3+ years research experience
  • Expertise in quantum programming languages (Qiskit, Cirq, Q#) and frameworks
  • Published work in quantum machine learning or related fields
  • Strong background in advanced mathematics (linear algebra, probability, optimization)
  • Experience with quantum hardware (superconducting, trapped ion, photonic)
  • Proficiency in Python, TensorFlow, and high-performance computing
  • Track record of translating theoretical research into practical applications

Required Skills

Quantum Computing Machine Learning AI Research Python TensorFlow Quantum Algorithms Cryptography Neural Networks

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