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Quantum Computing Research Scientist

FutureTech Innovations
San Francisco
Estimated Salary
USD 160.000 – USD 220.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Join our pioneering team at FutureTech Innovations as we redefine the boundaries of computational science. We're seeking a visionary Quantum Computing Research Scientist to lead breakthrough projects in quantum algorithms, error correction, and scalable architectures. Work with cutting-edge quantum processors at our state-of-the-art San Francisco lab and contribute to technologies that will shape 2026 and beyond.

This role offers unparalleled opportunities to collaborate with Nobel laureates, publish in top-tier journals, and develop patentable innovations. You'll receive competitive equity packages, flexible hybrid work arrangements, and a dedicated R&D budget of $500K annually.

Responsibilities

  • Design and implement novel quantum algorithms for optimization, cryptography, and machine learning applications
  • Lead research in quantum error correction techniques to achieve fault-tolerant systems
  • Develop scalable quantum architectures compatible with next-generation processors
  • Publish high-impact research in Nature/Science journals and present at IEEE Quantum Week
  • Mentor junior researchers and cross-functional engineering teams
  • Secure federal grants and industry partnerships for quantum computing initiatives

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field with 3+ years postdoc experience
  • Proven expertise in quantum programming languages (Q#, Quil, or Cirq)
  • Published research in quantum error correction or algorithm development
  • Familiarity with superconducting, photonic, or trapped-ion quantum systems
  • Strong background in linear algebra, probability theory, and complexity theory
  • Experience with cloud quantum platforms (IBM Quantum, Amazon Braket)
  • Ability to secure DoE or NSF grants preferred

Required Skills

Quantum Computing Quantum Algorithms Error Correction Q# Python Machine Learning Superconducting Systems Research Methodology

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