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Quantum Computing Research Scientist

NexTech Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
23 Mei 2026
Deadline
23 Mei 2027

Job Description

Join NexTech Innovations at the forefront of quantum revolution! We're pioneering next-gen quantum computing solutions that will redefine industries by 2026. As a Quantum Computing Research Scientist, you'll collaborate with Nobel laureates and industry disruptors to develop scalable quantum algorithms and error-correction protocols. Our state-of-the-art lab in downtown San Francisco offers unparalleled resources to accelerate quantum breakthroughs. We offer competitive equity packages, flexible work arrangements, and opportunities to publish in leading journals. Shape the future of technology while enjoying California's vibrant tech ecosystem.

Responsibilities

  • Design and implement quantum algorithms for optimization, cryptography, and machine learning applications
  • Develop novel error-correction techniques to achieve quantum supremacy
  • Collaborate with hardware teams to translate theoretical models into practical quantum systems
  • Lead research initiatives targeting 2026 quantum commercialization milestones
  • Publish findings in peer-reviewed journals and present at international conferences
  • Secure external funding through NSF and DoE grants
  • Mentor junior researchers in quantum physics and computational theory

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field
  • 3+ years of hands-on quantum algorithm development experience
  • Proficiency in quantum programming languages (Qiskit, Cirq, or Quipper)
  • Publication record in Nature/Science or equivalent top-tier journals
  • Expertise in quantum error correction and fault-tolerant architectures
  • Demonstrated ability to secure $500K+ in research funding
  • Strong background in linear algebra, probability theory, and computational complexity

Required Skills

Quantum Computing Quantum Algorithms Error Correction Qiskit Cirq Cryptography Machine Learning Theoretical Physics

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