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Quantum Computing Research Scientist

NexusLabs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

Join NexusLabs at the forefront of technological evolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking a visionary Quantum Computing Research Scientist to develop next-generation algorithms and hardware architectures that will redefine computational boundaries. Collaborate with Nobel laureates and industry disruptors in our state-of-the-art quantum research facility, where your work will directly shape the future of artificial intelligence, cryptography, and materials science. Enjoy unparalleled resources, flexible research parameters, and a culture that celebrates intellectual curiosity.

Responsibilities

  • Design and implement novel quantum algorithms for complex computational challenges
  • Lead hardware-software co-design initiatives for scalable quantum processors
  • Publish groundbreaking research in top-tier quantum computing journals
  • Develop error-correction protocols for fault-tolerant quantum systems
  • Mentor junior researchers and cross-functional engineering teams
  • Secure government and private sector research grants
  • Collaborate with AI teams to integrate quantum machine learning frameworks

Qualifications

  • PhD in Physics, Computer Science, or Quantum Information Science
  • 3+ years of hands-on quantum algorithm development experience
  • Proficiency with quantum programming languages (Qiskit, Cirq, Q#)
  • Publication record in Nature/Science or equivalent quantum computing venues
  • Deep understanding of quantum error correction and decoherence mitigation
  • Experience with superconducting or trapped-ion quantum systems
  • Strong background in linear algebra and computational complexity theory
  • Ability to translate theoretical concepts into practical implementations

Required Skills

Quantum Computing Quantum Algorithms Qiskit Cirq Quantum Error Correction Superconducting Systems Q# Machine Learning Cryptography Linear Algebra Research Grants

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