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Quantum Computing Research Scientist

Nexus Quantum Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
20 Mei 2026
Deadline
20 Mei 2027

Job Description

Join Nexus Quantum Labs at the forefront of technological evolution as we pioneer breakthroughs in quantum computing for 2026 and beyond. We seek a visionary Quantum Computing Research Scientist to develop next-generation algorithms and protocols that will redefine computational boundaries. In this role, you'll collaborate with Nobel laureates and industry pioneers in our state-of-the-art facility, solving complex problems in cryptography, materials science, and artificial intelligence. We offer unparalleled resources, competitive compensation, and the opportunity to shape humanity's technological future.

Responsibilities

  • Design and implement quantum algorithms for practical applications in cryptography and machine learning
  • Lead experimental research on quantum error correction and qubit stability
  • Collaborate with hardware teams to optimize quantum processor architectures
  • Publish findings in peer-reviewed journals and present at international conferences
  • Develop quantum-resistant security protocols for enterprise clients
  • Mentor junior researchers and drive cross-functional innovation projects
  • Secure patents for novel quantum computing methodologies

Qualifications

  • PhD in Physics, Computer Science, or Quantum Information Science with 5+ years of research experience
  • Proven track record in quantum algorithm development or quantum error correction
  • Expertise in quantum programming languages (Q#, Qiskit, or Cirq)
  • Strong background in linear algebra, probability theory, and computational complexity
  • Experience with quantum simulation tools and high-performance computing environments
  • Demonstrated ability to secure research funding and lead academic-industry collaborations
  • Publication record in top-tier quantum computing journals

Required Skills

Quantum Computing Qiskit Q# Cryptography Machine Learning Linear Algebra Research Methodology High-Performance Computing

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