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Quantum Computing Research Lead

Nexus Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
18 Mei 2026
Deadline
18 Mei 2027

Job Description

Join Nexus Innovations at the forefront of technological revolution! We're seeking a visionary Quantum Computing Research Lead to pioneer breakthroughs that will redefine computing by 2026. Lead a world-class team in developing quantum algorithms, error correction protocols, and scalable quantum architectures. Collaborate with Nobel laureates and industry disruptors to solve humanity's most complex challenges in cryptography, materials science, and artificial intelligence. This is your chance to shape the future of technology while enjoying unparalleled benefits including stock options, flexible remote work, and cutting-edge R&D resources.

Responsibilities

  • Design and implement quantum algorithms for practical industrial applications
  • Lead cross-functional teams of quantum physicists and software engineers
  • Develop error correction methodologies for fault-tolerant quantum systems
  • Secure $5M+ in research grants from NSF, DARPA, and private foundations
  • Publish top-tier papers in Nature/Science journals and present at IEEE Quantum Week
  • Drive commercialization of quantum solutions in finance and healthcare sectors
  • Maintain strategic partnerships with IBM, Google Quantum, and MIT's Center for Quantum Engineering

Qualifications

  • PhD in Quantum Computing, Physics, or Computer Science
  • 5+ years of hands-on quantum algorithm development experience
  • Published research in quantum error correction or quantum supremacy
  • Expertise in Qiskit, Cirq, or quantum circuit simulation frameworks
  • Proven track record of securing government or corporate research funding
  • Experience mentoring PhD-level researchers and managing technical teams
  • Deep understanding of NISQ-era limitations and fault-tolerance roadmaps

Required Skills

Quantum Computing Quantum Algorithms Error Correction Qiskit Cirq Research Leadership Machine Learning Cryptography

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