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Research & Development 🏢 Full Time ⭐️ Verified

Quantum Computing Research Scientist

Nexus Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
13 Mei 2026
Deadline
13 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 architect next-gen algorithms that will redefine computational boundaries. Our state-of-the-art lab in San Francisco offers unparalleled resources to transform theoretical breakthroughs into practical applications. This role combines deep scientific rigor with entrepreneurial drive in an environment where your ideas could shape humanity's technological future.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and machine learning applications
  • Lead experimental validation of quantum supremacy claims using superconducting qubit systems
  • Collaborate with cross-functional teams to develop quantum-resistant cryptography frameworks
  • Author breakthrough research papers for peer-reviewed journals and industry conferences
  • Secure $1M+ in research funding through NSF and DARPA proposals
  • Mentor PhD candidates in quantum information science
  • Drive commercialization of quantum computing patents

Qualifications

  • PhD in Physics, Computer Science, or Quantum Information with 3+ years industry experience
  • Published research in Nature/Science on quantum algorithms or error correction
  • Proficiency with Qiskit, Cirq, or equivalent quantum programming frameworks
  • Expertise in superconducting qubit manipulation and readout techniques
  • Track record of securing government or corporate research grants
  • Deep understanding of quantum decoherence mitigation strategies
  • Experience with cryogenic quantum hardware integration

Required Skills

Quantum Computing Superconducting Qubits Quantum Algorithms Cryogenics Qiskit DARPA Proposals Quantum Error Correction Machine Learning

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