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Quantum Computing Research Scientist

Nexus Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Join Nexus Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking visionary Quantum Computing Research Scientists to develop breakthrough algorithms, optimize qubit architectures, and solve previously unsolvable computational challenges. Our state-of-the-art facility in San Francisco offers unparalleled resources for cutting-edge research with direct impact on cryptography, drug discovery, and AI development.

As a key member of our Quantum Research Division, you'll collaborate with Nobel laureates, industry pioneers, and government agencies to shape the next generation of computational technology. We provide competitive compensation, flexible work arrangements, and opportunities to publish groundbreaking research in top-tier journals.

Responsibilities

  • Design and implement novel quantum algorithms for practical applications
  • Optimize qubit coherence and error correction protocols
  • Develop hybrid quantum-classical computing frameworks
  • Lead experimental validation of quantum systems
  • Collaborate with hardware teams on next-generation quantum processors
  • Secure patents and publish high-impact research
  • Mentor junior researchers and interns

Qualifications

  • PhD in Physics, Computer Science, or related field (or equivalent experience)
  • 3+ years of quantum computing research experience
  • Proficiency in quantum programming languages (Qiskit, Cirq, Q#)
  • Strong background in quantum information theory
  • Experience with superconducting or trapped-ion qubit systems
  • Published research in quantum computing or related fields
  • Excellent problem-solving and analytical abilities
  • Ability to work in cross-functional teams

Required Skills

Quantum Computing Quantum Algorithms Qiskit Cirq Q# Superconducting Qubits Quantum Error Correction Cryptography Machine Learning

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