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Quantum Computing Research Scientist

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

Job Description

Join Nexus Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. As a Quantum Computing Research Scientist, you'll design and implement next-gen quantum algorithms to solve previously unsolvable problems in cryptography, optimization, and machine learning. Our state-of-the-art facility in San Francisco offers unparalleled resources and a collaborative environment where your ideas will shape the future of computation.

Responsibilities

  • Develop novel quantum algorithms with practical applications for 2026-era challenges
  • Lead cross-functional teams in translating theoretical models into functional quantum circuits
  • Optimize quantum error correction protocols for scalable fault-tolerant systems
  • Collaborate with hardware engineers to bridge quantum software-hardware integration gaps
  • Publish breakthrough research in top-tier quantum computing journals and conferences
  • Secure competitive research grants from NSF, DARPA, and private foundations
  • Mentor junior researchers in quantum information theory and computational physics

Qualifications

  • PhD in Quantum Computing, Physics, Computer Science, or related field (or equivalent experience)
  • 3+ years hands-on experience with quantum programming frameworks (Qiskit, Cirq, Q#)
  • Expertise in quantum algorithm design and complexity theory
  • Published research in peer-reviewed quantum computing journals
  • Proficiency in high-performance computing environments and parallel processing
  • Demonstrated ability to secure research funding and lead technical projects
  • Strong background in linear algebra, probability, and information theory
  • Experience with quantum hardware interfaces (IBM Quantum, Rigetti, etc.)

Required Skills

Quantum Computing Qiskit Cirq Quantum Algorithms Quantum Error Correction High-Performance Computing Machine Learning Cryptography Theoretical Physics Research Methodology Parallel Processing

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