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Quantum Computing Research Scientist

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 quantum computing solutions for 2026 and beyond. As a Quantum Computing Research Scientist, you'll design next-generation algorithms and architectures that will redefine computational boundaries. Our Austin-based R&D hub offers unparalleled resources to translate theoretical breakthroughs into real-world applications across healthcare, logistics, and AI. Collaborate with Nobel laureates and industry disruptors in an environment where curiosity fuels innovation.

We offer competitive compensation, equity packages, and flexible work arrangements for top-tier talent. Your work will directly shape the technological landscape of the coming decade.

Responsibilities

  • Design and implement quantum algorithms for practical applications in 2026-era systems
  • Lead research on error correction and qubit stability in scalable quantum processors
  • Collaborate with hardware teams to optimize quantum-classical hybrid computing workflows
  • Publish breakthrough research in top-tier journals and industry whitepapers
  • Develop patentable quantum solutions for commercialization by 2026
  • Mentor junior researchers and contribute to lab's strategic roadmap

Qualifications

  • PhD in Quantum Computing, Physics, or Computer Science (or equivalent experience)
  • 3+ years of hands-on quantum algorithm development experience
  • Expertise in quantum programming frameworks (Qiskit, Cirq, or Q#)
  • Strong publication record in quantum computing or related fields
  • Deep understanding of quantum error correction and fault tolerance
  • Proven ability to translate theoretical concepts into practical implementations
  • Excellent communication skills for cross-functional collaboration

Required Skills

Quantum Computing Algorithm Design Qiskit Cirq Error Correction Quantum Mechanics Research Machine Learning

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