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Quantum Computing Research Lead

Nexus Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer breakthroughs in quantum computing for 2026 and beyond. We seek a visionary Quantum Computing Research Lead to architect next-gen quantum algorithms and scalable hardware solutions. This role offers unparalleled opportunities to shape the future of computational science while collaborating with Nobel laureates and industry pioneers in our state-of-the-art Austin facility. Enjoy competitive equity, flexible work arrangements, and dedicated R&D funding to transform theoretical concepts into revolutionary applications.

Responsibilities

  • Design and implement quantum algorithms for optimization, cryptography, and machine learning applications
  • Lead cross-functional teams of physicists, engineers, and software developers in quantum hardware development
  • Secure $5M+ in federal and private research grants for 2026 quantum initiatives
  • Publish findings in top-tier journals and present at international quantum conferences
  • Develop roadmaps for quantum advantage in commercial sectors (finance, pharma, logistics)
  • Maintain strategic partnerships with quantum hardware providers and cloud services
  • Mentor PhD researchers and drive quantum education programs

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field (Postdoc preferred)
  • 5+ years of hands-on quantum computing research with published peer-reviewed papers
  • Expertise in quantum circuit design, error correction, and decoherence mitigation
  • Proven track record of securing government or corporate research funding
  • Proficiency in quantum programming frameworks (Qiskit, Cirq, Q#)
  • Demonstrated experience leading multidisciplinary technical teams
  • Deep understanding of NISQ-era limitations and fault-tolerant architectures

Required Skills

Quantum Computing Quantum Algorithms Quantum Hardware Research Leadership Scientific Grants Error Correction Machine Learning Cryptography

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