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Information Technology 🏢 Full Time ⭐️ Verified

Quantum Computing Research Scientist

Nexus Quantum Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Join Nexus Quantum Labs at the forefront of 2026's technological revolution. We're pioneering quantum computing applications that will redefine industries worldwide. As a Research Scientist, you'll develop next-gen quantum algorithms and collaborate with world-class physicists to solve previously impossible computational challenges. Our state-of-the-art facility in San Francisco offers unparalleled resources for innovation, including access to 1000-qubit processors and exclusive industry partnerships. We offer competitive equity packages, flexible work arrangements, and a culture that values intellectual curiosity and breakthrough thinking.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and simulation problems
  • Lead experimental research on quantum error correction and coherence enhancement
  • Collaborate with hardware engineers to translate theoretical models into practical applications
  • Publish groundbreaking research in top-tier quantum computing journals and conferences
  • Mentor junior researchers and foster cross-functional innovation
  • Secure external funding through NSF and DARPA grant applications

Qualifications

  • PhD in Quantum Computing, Physics, or Computer Science (or equivalent experience)
  • 3+ years of hands-on quantum algorithm development experience
  • Proficiency with Qiskit, Cirq, or similar quantum programming frameworks
  • Published record in quantum information science or related fields
  • Deep understanding of quantum decoherence mitigation techniques
  • Experience with high-performance computing environments
  • Strong analytical skills and ability to communicate complex concepts

Required Skills

Quantum Computing Quantum Algorithms Qiskit Cirq Quantum Error Correction High-Performance Computing Research Machine Learning

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