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Quantum Computing Research Scientist

Nexus Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
12 Mei 2026
Deadline
12 Mei 2027

Job Description

Join Nexus Innovations at the forefront of technological evolution as we pioneer quantum computing breakthroughs for 2026 and beyond. We seek a visionary Quantum Computing Research Scientist to architect next-gen solutions that will redefine industries. You'll collaborate with Nobel laureates and industry disruptors in our state-of-the-art lab, solving complex optimization problems that were previously impossible. This role offers unparalleled opportunities to publish groundbreaking research and shape the future of computational science.

Our competitive package includes equity, flexible hybrid work, and dedicated innovation time. Be part of the team that's building the computational foundation for humanity's next technological leap.

Responsibilities

  • Design and implement quantum algorithms for practical 2026-era applications
  • Lead research in quantum error correction and fault-tolerant systems
  • Collaborate with hardware teams to optimize quantum circuit architectures
  • Develop proprietary quantum simulation frameworks for industry partners
  • Publish peer-reviewed research in top-tier quantum computing journals
  • Present findings at global conferences and industry summits
  • Secure patents for novel quantum methodologies

Qualifications

  • PhD in Physics, Computer Science, or related quantum field
  • 3+ years of hands-on quantum algorithm development experience
  • Expertise in Qiskit, Cirq, or equivalent quantum frameworks
  • Deep understanding of quantum entanglement and superposition principles
  • Publication record in Nature/Science or equivalent top-tier journals
  • Experience with superconducting or trapped-ion quantum systems
  • Strong background in linear algebra and quantum information theory

Required Skills

Quantum Computing Qiskit Cirq Quantum Algorithms Superconducting Systems Linear Algebra Python Research Methodology

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