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Quantum Computing Research Scientist

Nexus Labs
San Francisco
Estimated Salary
USD 150.000 – USD 200.000
New
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking visionary Quantum Computing Research Scientists to develop groundbreaking algorithms, optimize qubit stability, and solve computational problems previously deemed impossible. Our state-of-the-art facility in San Francisco offers unparalleled resources for pushing the boundaries of quantum mechanics and machine learning integration.

This role offers competitive equity packages, flexible work arrangements, and collaboration with Nobel laureates and industry pioneers. Shape the future of computing with us.

Responsibilities

  • Design and implement quantum algorithms for complex optimization problems
  • Develop error correction protocols to enhance qubit coherence times
  • Collaborate with hardware teams to integrate quantum-classical hybrid systems
  • Publish research in peer-reviewed journals and present at global conferences
  • Mentor junior researchers and drive quantum literacy initiatives
  • Secure government and private sector research grants
  • Partner with AI teams to develop quantum machine learning frameworks

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field
  • 3+ years of hands-on quantum algorithm development experience
  • Proficiency with quantum programming languages (Qiskit, Cirq, Q#)
  • Deep understanding of quantum error correction and fault tolerance
  • Published research in quantum computing or theoretical physics
  • Experience with superconducting qubit architectures or trapped ions
  • Strong background in linear algebra, probability, and information theory
  • US citizenship or permanent residency required for government contracts

Required Skills

Quantum Computing Quantum Algorithms Qiskit Cirq Quantum Error Correction Superconducting Qubits Theoretical Physics Machine Learning Research

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