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Quantum AI Research Scientist 2026

Nexus Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Join Nexus Innovations at the forefront of technological evolution as we pioneer the next generation of quantum-AI integration. We're seeking a visionary Quantum AI Research Scientist to architect breakthrough solutions that will redefine industries by 2026. This role combines quantum computing expertise with machine learning innovation to solve humanity's most complex challenges.

Our state-of-the-art facility in San Francisco offers an unparalleled environment for collaboration with Nobel laureates and industry pioneers. You'll lead cross-functional teams to develop quantum neural networks, design fault-tolerant quantum algorithms, and create commercial applications for quantum supremacy.

Responsibilities

  • Design and implement quantum machine learning models for 2026-era applications
  • Lead research on quantum error correction and coherence optimization
  • Develop hybrid quantum-classical AI frameworks for enterprise solutions
  • Collaborate with hardware teams to translate theoretical models into practical implementations
  • Publish findings in top-tier journals and present at international conferences
  • Mentor junior researchers and drive innovation through hackathons and prototyping

Qualifications

  • PhD in Quantum Computing, Physics, or Computer Science (or equivalent experience)
  • 3+ years in quantum algorithm development or quantum machine learning
  • Proficiency with quantum programming frameworks (Qiskit, Cirq, or Q#)
  • Published research in quantum computing or AI (arXiv/IEEE journals)
  • Deep understanding of quantum entanglement and superposition principles
  • Experience with high-performance computing and GPU acceleration
  • Strong background in linear algebra, probability, and information theory

Required Skills

Quantum Computing Machine Learning Qiskit Cirq Q# Neural Networks Algorithm Design High-Performance Computing Python TensorFlow PyTorch

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