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Quantum Computing Research Scientist

Nexus Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
11 Mei 2026
Deadline
11 Mei 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 a visionary Quantum Computing Research Scientist to develop next-gen algorithms and protocols that will redefine computational boundaries. Collaborate with Nobel laureates and industry pioneers in our state-of-the-art Silicon Valley facility, where breakthrough ideas become reality. This role offers unparalleled resources, competitive compensation, and the opportunity to shape humanity's digital future.

Responsibilities

  • Design and implement quantum algorithms for optimization problems in cryptography and machine learning
  • Lead experimental validation of quantum protocols using superconducting qubit platforms
  • Develop error correction frameworks to achieve fault-tolerant quantum computation
  • Collaborate with hardware teams to co-design quantum-classical hybrid systems
  • Publish peer-reviewed research and present findings at premier conferences
  • Secure $5M+ in government and industry research funding
  • Mentor PhD candidates and postdoctoral researchers

Qualifications

  • PhD in Physics, Computer Science, or related field with quantum computing specialization
  • 3+ years of hands-on experience with quantum programming languages (Q#, Qiskit, Cirq)
  • Published research in Nature/Science or top-tier quantum computing journals
  • Proficiency in quantum circuit design and quantum error correction techniques
  • Deep understanding of quantum mechanics foundations and decoherence mechanisms
  • Experience with cryogenic quantum hardware systems
  • Strong track record of interdisciplinary collaboration
  • US citizenship or permanent residency required for government contracts

Required Skills

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

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