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Quantum Computing Research Lead 2026

Nexus Quantum Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Join Nexus Quantum Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. We seek a visionary Research Lead to architect next-gen quantum systems that will redefine industries. This role offers unparalleled access to cutting-edge hardware, a collaborative environment with Nobel laureates, and the opportunity to shape humanity's technological future.

Our team operates at the intersection of theoretical physics and practical application, developing quantum algorithms that solve previously impossible problems in cryptography, materials science, and artificial intelligence. You'll lead a multidisciplinary team of physicists, engineers, and software architects in our state-of-the-art San Francisco facility.

Responsibilities

  • Lead quantum algorithm development for 2026-era computational challenges
  • Architect scalable quantum systems with error correction capabilities
  • Collaborate with hardware teams on quantum processor optimization
  • Publish breakthrough research in top-tier quantum computing journals
  • Develop intellectual property portfolio covering quantum methodologies
  • Mentor junior researchers in quantum information theory
  • Drive partnerships with academic institutions and industry leaders

Qualifications

  • PhD in Quantum Computing, Physics, or Computer Science
  • 5+ years of quantum algorithm development experience
  • Expertise in quantum error correction protocols
  • Published research in quantum information theory
  • Proficiency with quantum programming frameworks (Qiskit, Cirq)
  • Strong background in quantum hardware architectures
  • Track record of leading cross-functional technical teams
  • Demonstrated ability to secure research funding

Required Skills

Quantum Computing Quantum Algorithms Error Correction Qiskit Cirq Quantum Hardware Cryptography Machine Learning Superconducting Qubits

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