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Quantum Computing Research Scientist

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

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer quantum computing solutions for 2026 and beyond. We seek a visionary Quantum Computing Research Scientist to develop breakthrough algorithms and protocols that will redefine computational boundaries. Collaborate with Nobel laureates and industry pioneers in our state-of-the-art facility overlooking the Bay.

This role offers unparalleled opportunities to shape the future of cryptography, AI optimization, and molecular modeling. You'll work with cutting-edge quantum hardware while contributing to open-source frameworks that will power the next decade of scientific discovery.

Responsibilities

  • Design and implement novel quantum algorithms for practical industrial applications
  • Lead cross-functional teams in developing error-corrected quantum systems
  • Author peer-reviewed publications and patent quantum methodologies
  • Optimize quantum circuits for real-world problem-solving in finance and biotech
  • Mentor junior researchers in quantum information theory
  • Develop hybrid quantum-classical computing frameworks
  • Collaborate with hardware teams on qubit stabilization techniques

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field
  • 3+ years of hands-on quantum algorithm development experience
  • Expertise in Qiskit, Cirq, or equivalent quantum programming frameworks
  • Publication record in top-tier quantum computing journals
  • Deep understanding of quantum error correction protocols
  • Proficiency in Python, C++, and quantum circuit design
  • Demonstrated ability to translate theoretical concepts into practical solutions
  • Experience with cloud-based quantum computing platforms (IBM Quantum, AWS Braket)

Required Skills

Quantum Computing Quantum Algorithms Qiskit Cirq Quantum Error Correction Python C++ Cryptography Machine Learning

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