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Quantum Computing Researcher

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
19 Mei 2026
Deadline
19 Mei 2027

Job Description

Join Nexus Future Labs at the forefront of technological evolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking visionary researchers to develop next-generation algorithms that will redefine computational boundaries. Our state-of-the-art facility in San Francisco's Innovation District offers unparalleled resources for breakthrough work in quantum cryptography, error correction, and machine learning integration.

This role provides competitive compensation, equity, and the opportunity to collaborate with Nobel laureates and industry pioneers. You'll contribute to projects with real-world impact across healthcare, logistics, and renewable energy sectors.

Responsibilities

  • Design and implement novel quantum algorithms for complex optimization problems
  • Lead experimental validation of quantum supremacy claims on proprietary hardware
  • Develop hybrid quantum-classical frameworks for enterprise applications
  • Publish groundbreaking research in top-tier journals and conferences
  • Collaborate with hardware engineering teams to co-design quantum processors
  • Mentor junior researchers and secure competitive research grants
  • Present findings to industry stakeholders and government agencies

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field
  • 3+ years of hands-on quantum algorithm development experience
  • Publication record in Nature/Science or equivalent tier journals
  • Expertise in quantum programming languages (Qiskit, Cirq, or Q#)
  • Strong background in linear algebra and probability theory
  • Proficiency with high-performance computing environments
  • Experience with machine learning frameworks (TensorFlow/PyTorch)
  • Clearance for government-sponsored research projects preferred

Required Skills

Quantum Computing Algorithm Design Quantum Cryptography Qiskit Machine Learning High-Performance Computing Linear Algebra Cryptography

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