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Quantum Computing Research Scientist

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

Job Description

Join Nexus Quantum Labs at the forefront of technological evolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking visionary Quantum Computing Research Scientists to develop groundbreaking algorithms and architectures that will redefine computational boundaries. Our multidisciplinary team operates at the intersection of physics, computer science, and AI, tackling challenges in cryptography, optimization, and material science. Enjoy competitive compensation, flexible work arrangements, and access to cutting-edge quantum hardware at our state-of-the-art San Francisco facility.

Responsibilities

  • Design and implement novel quantum algorithms for real-world applications
  • Lead research in quantum error correction and fault-tolerant systems
  • Collaborate with hardware engineers to optimize quantum circuit performance
  • Publish findings in peer-reviewed journals and present at international conferences
  • Develop quantum machine learning frameworks for predictive analytics
  • Mentor junior researchers and cross-functional engineering teams
  • Secure and manage research grants from government and private sector partners

Qualifications

  • PhD in Physics, Computer Science, or related quantum discipline
  • 3+ years of hands-on quantum algorithm development experience
  • Proficiency in quantum programming languages (Qiskit, Cirq, or Q#)
  • Deep understanding of quantum entanglement and superposition principles
  • Publication record in quantum computing or high-energy physics
  • Experience with cloud-based quantum computing platforms (IBM Quantum, Rigetti)
  • Strong analytical skills and ability to translate complex theoretical concepts
  • US citizenship or permanent residency required for government contract work

Required Skills

Quantum Computing Quantum Algorithms Qiskit Cirq Quantum Error Correction Machine Learning Cryptography High-Performance Computing

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