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Quantum Computing Research Lead 2026

Nexus Quantum Labs
Austin
Estimated Salary
USD 190.000 – USD 280.000
Live Update
14 Mei 2026
Deadline
14 Mei 2027

Job Description

Join the forefront of technological revolution at Nexus Quantum Labs as we pioneer the next generation of quantum computing solutions. We seek a visionary Research Lead to architect breakthrough systems that will redefine computational boundaries by 2026. This role offers unparalleled opportunity to shape humanity's digital future while collaborating with Nobel laureates and industry pioneers in our state-of-the-art Austin facility.

Our hybrid model combines cutting-edge lab work with flexible remote options, offering competitive equity packages and comprehensive wellness benefits. You'll lead a multidisciplinary team developing fault-tolerant quantum processors, quantum AI algorithms, and next-gen cryptography protocols.

Responsibilities

  • Architect quantum computing frameworks targeting 2026 commercial deployment milestones
  • Lead cross-functional teams of physicists, engineers, and AI specialists
  • Develop quantum error correction protocols achieving >99.9% fidelity
  • Secure $15M+ in research grants from NSF and DoD programs
  • Publish 3+ breakthrough papers in Nature/Science journals annually
  • Collaborate with Intel and IBM on quantum-classical hybrid systems
  • Mentor postdocs and PhD candidates in quantum algorithms research

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field
  • 5+ years experience in quantum computing R&D
  • Published research in top-tier quantum computing journals
  • Expertise in quantum error correction and fault tolerance
  • Proficiency in Qiskit, Cirq, and quantum circuit optimization
  • Track record of securing government/industry research funding
  • Strong background in quantum machine learning applications
  • Experience leading teams of 10+ technical researchers

Required Skills

Quantum Computing Quantum Algorithms Fault Tolerance Qiskit Cirq Quantum Error Correction Machine Learning Research Leadership Scientific Grant Writing

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