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Quantum Computing Research Scientist

Nexus Labs
Austin
Estimated Salary
USD 150.000 – USD 220.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Join Nexus Labs at the forefront of 2026's technological revolution. We're pioneering quantum computing solutions that will redefine industries, and we seek a visionary Research Scientist to lead breakthrough innovations in quantum algorithms and error correction. Work alongside Nobel laureates in our state-of-the-art Austin facility, where you'll develop next-gen quantum systems that solve previously unsolvable problems in cryptography, materials science, and artificial intelligence.

This role offers unparalleled resources for groundbreaking research, including access to our 512-qubit quantum processor and collaboration with Fortune 500 partners in healthcare, aerospace, and finance. Your work will directly shape the technological landscape of the next decade.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and machine learning applications
  • Lead research in quantum error correction techniques for fault-tolerant systems
  • Collaborate with hardware engineers to optimize quantum circuit performance
  • Publish findings in top-tier journals and present at international conferences
  • Develop quantum software frameworks for commercial applications
  • Mentor junior researchers and drive cross-functional innovation projects

Qualifications

  • PhD in Physics, Computer Science, or related field with quantum computing focus
  • 3+ years of hands-on quantum algorithm development experience
  • Expertise in quantum error correction and fault tolerance
  • Proficiency with quantum programming frameworks (Qiskit, Cirq, or Q#)
  • Strong publication record in quantum information science
  • Experience with high-performance computing and parallel processing
  • Ability to translate complex quantum concepts into practical solutions

Required Skills

Quantum Computing Quantum Algorithms Error Correction Qiskit Cirq Machine Learning High-Performance Computing

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