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Quantum Computing Research Scientist

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

Job Description

Join Nexus Quantum Labs at the forefront of technological innovation as we pioneer the next generation of computing solutions. We're seeking a visionary Quantum Computing Research Scientist to develop breakthrough algorithms and systems that will redefine industries by 2026. Collaborate with Nobel laureates and industry pioneers in our state-of-the-art Austin facility, where you'll contribute to projects spanning quantum cryptography, optimization, and simulation. This role offers unparalleled resources, competitive compensation, and the opportunity to shape the quantum revolution.

Responsibilities

  • Design and implement quantum algorithms for complex optimization problems
  • Lead research on quantum error correction techniques for scalable systems
  • Develop hybrid quantum-classical computing frameworks
  • Collaborate with hardware teams to translate theoretical models into practical implementations
  • Publish findings in leading journals and present at international conferences
  • Mentor junior researchers and drive cross-functional innovation
  • Secure patents and intellectual property for breakthrough discoveries

Qualifications

  • PhD in Quantum Computing, Physics, or related field (or equivalent experience)
  • 3+ years of hands-on quantum algorithm development experience
  • Proficiency in quantum programming frameworks (Qiskit, Cirq, or Q#)
  • Strong background in linear algebra, quantum mechanics, and computational complexity
  • Track record of peer-reviewed publications in quantum computing
  • Demonstrated ability to collaborate across interdisciplinary teams
  • Experience with high-performance computing environments
  • Passion for solving humanity's grand challenges through quantum technology

Required Skills

Quantum Computing Algorithm Development Quantum Programming Error Correction Hybrid Computing Research Machine Learning Cryptography

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