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Quantum Computing Research Scientist

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

Job Description

Join Nexus Quantum Labs at the forefront of 2026's technological revolution. We're pioneering quantum computing solutions that will redefine industries worldwide. As a Research Scientist, you'll collaborate with Nobel laureates and MIT alumni to develop next-gen quantum algorithms and error-correction protocols. Our state-of-the-art facility in San Francisco's Innovation District offers unmatched resources and a culture that celebrates bold experimentation.

We provide competitive equity packages, unlimited wellness stipends, and flexible remote options for top talent. This is your opportunity to shape the quantum landscape before it transforms global business.

Responsibilities

  • Design and implement novel quantum algorithms for cryptography and optimization problems
  • Lead experimental validation of quantum supremacy claims using superconducting qubits
  • Develop error-correction frameworks for fault-tolerant quantum systems
  • Collaborate with hardware teams to improve qubit coherence times
  • Publish breakthrough research in Nature Physics and IEEE journals
  • Secure $5M+ in DARPA and NSF research grants
  • Mentor PhD candidates in quantum information science

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field (or equivalent industry breakthrough)
  • 3+ years of hands-on quantum algorithm development experience
  • Published research in top-tier quantum computing publications
  • Proficiency in Qiskit, Cirq, or similar quantum SDKs
  • Demonstrated expertise in quantum error correction techniques
  • Experience with cryogenic quantum computing systems
  • Strong background in machine learning for quantum applications
  • Track record of translating theoretical models into experimental prototypes

Required Skills

Quantum Computing Quantum Algorithms Error Correction Qiskit Cirq Cryogenics Machine Learning Cryptography

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