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Quantum AI Research Lead - 2026 Vision

Nexus Quantum Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Join Nexus Quantum Dynamics at the forefront of 2026's technological revolution. We're pioneering quantum-AI convergence to solve humanity's most complex challenges. As our Research Lead, you'll architect next-generation algorithms that bridge quantum computing and artificial intelligence, transforming industries from healthcare to climate science. Our state-of-the-art lab offers unparalleled resources to push the boundaries of computational possibility.

We value visionary thinkers who thrive at the intersection of physics and machine learning. Your work will directly shape how society leverages quantum-AI solutions by 2026, creating sustainable impact across global ecosystems. If you're passionate about solving problems that don't yet have solutions, this is your moment to redefine what's possible.

Responsibilities

  • Design and implement quantum-AI hybrid algorithms for exponential computational advantage
  • Lead cross-functional teams of quantum physicists and ML engineers to prototype 2026-ready solutions
  • Develop error-correction frameworks for practical quantum neural networks
  • Collaborate with Fortune 500 partners to deploy quantum-AI use cases in logistics and drug discovery
  • Secure $5M+ in research grants for quantum-AI frontier projects
  • Publish breakthrough findings in Nature Quantum and IEEE journals
  • Mentor PhD candidates in quantum machine learning at our 2026 Innovation Center

Qualifications

  • PhD in Quantum Computing, Machine Learning, or Computational Physics
  • 5+ years experience in quantum algorithm development or AI research leadership
  • Published work in top-tier quantum/AI conferences (e.g., QIP, NeurIPS)
  • Proficiency in Qiskit, Cirq, and quantum cloud platforms (IBM, Rigetti)
  • Expertise in tensor networks and quantum machine learning frameworks
  • Proven track record of securing government/industry research funding
  • Strong background in complex system optimization and fault-tolerant quantum architectures
  • Experience translating theoretical research into commercial applications

Required Skills

Quantum Computing Machine Learning Python TensorFlow PyTorch Qiskit Cirq Quantum Algorithms AI Research Computational Physics Tensor Networks Quantum Machine Learning Fault-Tolerant Systems

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