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Quantum Computing Research Scientist

Nexus Quantum Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
21 Mei 2026
Deadline
21 Mei 2027

Job Description

Join Nexus Quantum Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking visionary Quantum Computing Research Scientists to develop groundbreaking algorithms, optimize quantum systems, and solve previously unsolvable computational challenges. This role offers unparalleled access to cutting-edge quantum hardware and collaborative research environments where your innovations will shape the future of computing.

Our state-of-the-art facility in San Francisco provides dynamic workspaces, flexible hours, and comprehensive benefits including equity packages. You'll collaborate with Nobel laureates and industry pioneers while contributing to projects that redefine human potential through quantum mechanics.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and simulation problems
  • Develop error correction protocols for scalable quantum systems
  • Collaborate with hardware teams to prototype and validate quantum circuits
  • Publish research in peer-reviewed journals and present at international conferences
  • Mentor junior researchers and drive cross-functional innovation initiatives
  • Secure research grants and patents for quantum computing breakthroughs

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field
  • 3+ years of hands-on quantum algorithm development experience
  • Proficiency in quantum programming languages (Q#, Qiskit, Cirq)
  • Deep understanding of quantum error correction and fault tolerance
  • Publication record in quantum computing or theoretical physics
  • Experience with high-performance computing environments
  • Strong analytical skills with ability to solve complex abstract problems

Required Skills

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

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