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Quantum Computing Research Scientist

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

Job Description

Join Nexus Quantum Labs at the forefront of technological revolution as we pioneer quantum computing solutions that will define 2026 and beyond. We're seeking visionary research scientists to develop breakthrough algorithms and protocols that will unlock unprecedented computational power. Our state-of-the-art facility in San Francisco offers unparalleled resources for innovation, including access to next-gen quantum processors and collaborative AI systems. This is your opportunity to shape the future of computing while working with world-class experts in a dynamic, forward-thinking environment.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and machine learning applications
  • Develop error mitigation protocols for quantum hardware scalability
  • Collaborate with AI systems to create hybrid quantum-classical computing frameworks
  • Lead research initiatives in topological quantum computing and fault-tolerant architectures
  • Publish findings in leading scientific journals and present at international conferences
  • Mentor junior researchers and cross-functional engineering teams
  • Secure external funding through government grants and industry partnerships

Qualifications

  • PhD in Quantum Computing, Physics, Computer Science, or related field
  • 3+ years of hands-on experience with quantum algorithm development
  • Proficiency in quantum programming languages (Q#, Qiskit, Cirq)
  • Deep understanding of quantum error correction and fault tolerance
  • Publication record in peer-reviewed quantum computing research
  • Expertise in machine learning and high-performance computing
  • Strong analytical skills with ability to solve complex theoretical problems
  • Experience with quantum hardware platforms (IBM Quantum, Rigetti, etc.)

Required Skills

Quantum Computing Quantum Algorithms Machine Learning Error Correction Fault Tolerance Qiskit Q# High-Performance Computing AI Integration

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