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2026 Quantum Computing Research Lead

Nexus Quantum Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
22 Mei 2026
Deadline
22 Mei 2027

Job Description

Join Nexus Quantum Labs at the forefront of technological evolution as we pioneer quantum computing solutions for 2026. We're seeking a visionary Research Lead to drive breakthroughs in quantum algorithms, cryptography, and scalable hardware integration. This role offers unparalleled opportunity to shape the next generation of computational paradigms while collaborating with Nobel laureates and industry disruptors.

Our state-of-the-art facility in San Francisco provides an immersive environment where innovation thrives. You'll lead a multidisciplinary team of physicists, engineers, and data scientists to overcome quantum decoherence challenges and develop fault-tolerant systems that will revolutionize industries from pharmaceuticals to aerospace.

Responsibilities

  • Lead quantum algorithm research for 2026 commercial applications
  • Design fault-tolerant quantum architectures targeting 1000+ qubit systems
  • Collaborate with hardware teams to optimize quantum processor performance
  • Develop quantum-resistant cryptographic protocols for next-gen security
  • Secure $5M+ in research funding through NSF and DARPA proposals
  • Mentor PhD researchers in quantum information science
  • Publish findings in Nature Physics and IEEE journals

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field
  • 5+ years of quantum computing R&D experience
  • Published research in top-tier quantum journals
  • Expertise in Qiskit, Cirq, or similar quantum frameworks
  • Deep understanding of quantum error correction techniques
  • Experience with superconducting qubit systems
  • Proven track record of securing government research grants
  • Strong background in machine learning for quantum optimization

Required Skills

Quantum Computing Quantum Algorithms Quantum Cryptography Superconducting Qubits Qiskit Cirq Fault-Tolerant Systems Machine Learning Research Leadership

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