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Information Technology 🏢 Full Time ⭐️ Verified

Quantum Computing Research Scientist

FutureTech Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Shape the future of technology as a Quantum Computing Research Scientist at FutureTech Innovations. Join our elite team to develop groundbreaking quantum algorithms and solutions that will revolutionize industries by 2026. Located in the heart of San Francisco's innovation hub, you'll work with state-of-the-art hardware and collaborate with world-class researchers to solve humanity's most complex challenges. We offer competitive compensation, flexible work arrangements, and opportunities to publish in top-tier scientific journals.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and machine learning applications
  • Collaborate with hardware teams to develop error-corrected quantum systems
  • Lead research initiatives in quantum cryptography and secure communications
  • Publish findings in peer-reviewed journals and present at international conferences
  • Mentor junior researchers and cross-functional engineering teams
  • Secure research funding through government grants and industry partnerships
  • Translate theoretical models into practical quantum computing solutions

Qualifications

  • PhD in Physics, Computer Science, or related field with quantum computing specialization
  • 3+ years of experience with quantum programming languages (Q#, Qiskit, or Cirq)
  • Deep understanding of quantum algorithms and complexity theory
  • Strong background in linear algebra, probability, and information theory
  • Proven track record of published quantum computing research
  • Experience with quantum simulation frameworks and hardware platforms
  • Demonstrated ability to lead complex technical projects
  • Excellent communication skills for technical and non-technical audiences

Required Skills

Quantum Computing Qiskit Q# Algorithm Design Cryptography Machine Learning Linear Algebra Research Leadership

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