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Quantum Computing Research Scientist

Nexus Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
21 Mei 2026
Deadline
21 Mei 2027

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer quantum computing solutions for 2026 and beyond. We seek a visionary Quantum Computing Research Scientist to develop groundbreaking algorithms and protocols that will redefine computational boundaries. In this role, you'll collaborate with world-class physicists and engineers in our state-of-the-art Austin facility, leveraging our quantum annealing supercomputers to solve previously intractable problems in cryptography, materials science, and AI optimization. We offer competitive compensation, flexible work arrangements, and access to our $50M annual R&D fund.

Responsibilities

  • Design and implement novel quantum algorithms for real-world applications
  • Lead experimental validation of quantum protocols on D-Wave and IBM quantum systems
  • Develop error-correction frameworks to achieve fault-tolerant quantum computation
  • Collaborate with AI teams to integrate quantum accelerators into machine learning pipelines
  • Secure federal and private research grants totaling $1M+ annually
  • Mentor cross-functional teams in quantum principles and applications
  • Publish findings in Nature/Science journals and present at IEEE Quantum Week

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field with 5+ years industry experience
  • Proven expertise in quantum gate operations and circuit optimization
  • Proficiency in Qiskit, Cirq, and quantum assembly languages
  • Published research in top-tier quantum computing journals
  • Experience with quantum hardware calibration and noise mitigation
  • Strong background in linear algebra and complex probability theory
  • Ability to translate theoretical concepts into practical quantum solutions

Required Skills

quantum computing quantum algorithms quantum annealing Qiskit Cirq quantum error correction quantum cryptography machine learning theoretical physics

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