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Quantum Computing Research Scientist

Nexus Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
1 Juni 2026
Deadline
1 Jun 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 groundbreaking algorithms and systems that will redefine computational boundaries. In this role, you'll collaborate with Nobel laureates and industry pioneers to solve humanity's most complex challenges in cryptography, materials science, and AI optimization. Our state-of-the-art quantum lab in San Francisco offers unparalleled resources, including 512-qubit processors and cryogenic computing infrastructure. If you're ready to shape the future of technology, this is your calling.

Responsibilities

  • Design and implement novel quantum algorithms for practical applications
  • Lead experimental quantum computing projects using superconducting qubit systems
  • Develop error correction protocols to enhance quantum coherence times
  • Collaborate with AI teams to integrate quantum machine learning models
  • Publish peer-reviewed research in top-tier journals and conferences
  • Secure research grants and patents for quantum innovations
  • Mentor junior researchers and foster cross-disciplinary collaboration

Qualifications

  • PhD in Quantum Computing, Physics, or Computer Science
  • 3+ years of hands-on quantum algorithm development experience
  • Proficiency in Qiskit, Cirq, or equivalent quantum programming frameworks
  • Deep understanding of quantum entanglement and superposition principles
  • Publication record in Nature, Science, or IEEE journals
  • Expertise in cryogenic systems and quantum control electronics
  • Strong background in linear algebra and complex analysis
  • Ability to translate theoretical concepts into experimental prototypes

Required Skills

Quantum Computing Qiskit Cirq Superconducting Qubits Quantum Algorithms Cryogenics Machine Learning Linear Algebra

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