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Quantum Computing Research Scientist

Nexus Quantum Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
21 Mei 2026
Deadline
21 Mei 2027

Job Description

Join Nexus Quantum Labs at the forefront of computational revolution! We're pioneering the next generation of quantum systems that will redefine 2026's technological landscape. As a Quantum Computing Research Scientist, you'll develop novel algorithms, optimize quantum circuits, and collaborate with world-class physicists to solve previously impossible problems. Our state-of-the-art lab in San Francisco offers unparalleled resources and a culture where innovation thrives. This role requires deep expertise in quantum mechanics and programming, with opportunities to publish groundbreaking research and shape the future of computing.

Responsibilities

  • Design and implement quantum algorithms for complex optimization problems
  • Develop error correction protocols for scalable quantum systems
  • Collaborate with hardware teams to translate theoretical models into practical implementations
  • Lead research initiatives in quantum machine learning applications
  • Publish findings in top-tier journals and present at international conferences
  • Mentor junior researchers and contribute to patent development
  • Stay current with emerging quantum technologies and industry standards

Qualifications

  • PhD in Physics, Computer Science, or related field with quantum focus
  • 3+ years of hands-on quantum computing experience with platforms like IBM Q or Rigetti
  • Proficiency in quantum programming languages (Qiskit, Cirq, Q#)
  • Strong background in linear algebra, probability theory, and quantum mechanics
  • Demonstrated ability to publish peer-reviewed research
  • Experience with high-performance computing environments
  • Excellent problem-solving skills and cross-functional collaboration ability
  • Preferred: Start-up experience and quantum hardware knowledge

Required Skills

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

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