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Information Technology 🏢 Full Time ⭐️ Verified

Quantum Computing Research Scientist

Nexus Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
2 Juni 2026
Deadline
2 Jun 2027

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer quantum computing solutions that will redefine industries by 2026. We seek visionary research scientists to develop next-generation quantum algorithms and hardware architectures. Our state-of-the-art facility in San Francisco offers an unparalleled environment for innovation, collaboration, and groundbreaking research.

This role offers the unique opportunity to shape the future of computing while working alongside Nobel laureates and industry pioneers. We provide competitive compensation, comprehensive benefits, and flexible work arrangements to support your professional growth and personal well-being.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and simulation problems
  • Lead research on quantum error correction techniques for scalable systems
  • Collaborate with hardware teams to develop quantum processor architectures
  • Publish findings in top-tier journals and present at international conferences
  • Secure external funding through government grants and industry partnerships
  • Mentor junior researchers and contribute to technical roadmap planning

Qualifications

  • PhD in Physics, Computer Science, or related field (or equivalent experience)
  • 3+ years of hands-on quantum computing research experience
  • Expertise in quantum algorithm design and complexity analysis
  • Proficiency with quantum simulation frameworks (Qiskit, Cirq, etc.)
  • Demonstrated ability to publish peer-reviewed research
  • Strong background in linear algebra, probability, and information theory
  • Excellent communication skills for technical and non-technical audiences

Required Skills

Quantum Computing Algorithm Design Quantum Error Correction Research Methodology Scientific Publishing Python Linear Algebra Machine Learning

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