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2026 Quantum AI Research Lead

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

Job Description

Join Nexus Labs at the forefront of technological evolution. We're pioneering the convergence of quantum computing and artificial intelligence to redefine human capabilities by 2026. As our 2026 Quantum AI Research Lead, you'll architect breakthrough systems that solve previously unsolvable problems in medicine, climate science, and computational modeling. This role offers unparalleled resources, a world-class team of Nobel laureates and MIT alumni, and the autonomy to shape the next decade of innovation.

Our state-of-the-art facility in San Francisco features quantum processors cooled to absolute zero, exascale computing clusters, and unlimited research budgets. We offer comprehensive benefits including equity, relocation assistance, and flexible work arrangements.

Responsibilities

  • Lead cross-functional teams in developing quantum neural networks for 2026-era applications
  • Design and implement fault-tolerant quantum algorithms achieving 99.9% fidelity
  • Collaborate with DARPA and NASA on classified national security projects
  • Publish 5+ high-impact papers in Nature/Science journals annually
  • Secure $10M+ in government and private research grants
  • Mentor PhD candidates and postdoctoral researchers
  • Present breakthrough findings at global tech summits including Web Summit and CES

Qualifications

  • PhD in Quantum Computing, AI, or Computational Physics from Tier 1 institution
  • 5+ years experience with superconducting qubit systems and Qiskit framework
  • Published research in quantum machine learning or quantum error correction
  • Expertise in tensor networks and quantum circuit optimization
  • Proven track record of securing federal research grants
  • Strong background in Python/C++ with GPU acceleration experience
  • Clearance for DoD projects or ability to obtain TS/SCI

Required Skills

Quantum Computing Artificial Intelligence Machine Learning Qiskit TensorFlow PyTorch Fault-Tolerant Systems Neural Networks Research Leadership Grant Writing High-Performance Computing

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