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Quantum Computing Research Scientist

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

Job Description

Join Nexus Quantum Labs at the forefront of technological revolution as we pioneer the next generation of quantum computing solutions. We're seeking visionary research scientists to develop breakthrough algorithms and systems that will redefine computational boundaries by 2026. Our state-of-the-art facility in San Francisco offers an unparalleled environment for innovation, collaboration, and impact. Work alongside Nobel Prize-winning physicists and top-tier engineers to solve humanity's most complex challenges—from drug discovery to climate modeling. We offer competitive compensation, equity, and flexible work arrangements for exceptional talent.

Responsibilities

  • Design and implement quantum algorithms for practical applications in cryptography, optimization, and machine learning
  • Lead cutting-edge research in quantum error correction and fault-tolerant systems
  • Collaborate with hardware teams to prototype and validate quantum processors
  • Publish findings in top-tier journals and present at international conferences
  • Secure research funding through NSF, DARPA, and industry partnerships
  • Mentor junior researchers and drive quantum literacy initiatives

Qualifications

  • PhD in Physics, Computer Science, Mathematics, or related field (or equivalent industry experience)
  • 3+ years of hands-on quantum computing research experience with published papers
  • Proficiency in quantum programming languages (Qiskit, Cirq, Q#) and simulation frameworks
  • Strong background in quantum information theory and quantum algorithms
  • Experience with superconducting or trapped-ion quantum systems preferred
  • Demonstrated ability to secure competitive research grants
  • Exceptional problem-solving skills and innovative mindset

Required Skills

Quantum Computing Quantum Algorithms Qiskit Cirq Quantum Error Correction Cryptography Machine Learning Superconducting Systems Trapped Ions Research Methodology

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