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Quantum Computing Research Scientist

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Join Nexus Future Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. Our interdisciplinary team is developing next-gen algorithms to solve previously unsolvable challenges in cryptography, materials science, and AI optimization. We offer unparalleled resources, flexible work arrangements, and the opportunity to shape humanity's technological future.

Why Nexus Future Labs? We combine cutting-edge research with startup agility, backed by $500M in venture funding. Our state-of-the-art quantum lab features 256-qubit processors and partnerships with MIT, Stanford, and NASA. Enjoy competitive equity packages, wellness stipends, and dedicated innovation time.

Responsibilities

  • Design and implement quantum algorithms for real-world applications
  • Lead research in error correction and quantum coherence optimization
  • Collaborate with AI teams to develop hybrid quantum-classical models
  • Publish breakthrough findings in Nature/Science journals
  • Present findings at IEEE Quantum Week and Davos Tech Summit
  • Mentor junior researchers in quantum theory and experimental protocols
  • Secure patents for novel quantum computing methodologies

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field
  • 3+ years of hands-on quantum computing experience
  • Proficiency in Qiskit, Cirq, or similar quantum frameworks
  • Published research in peer-reviewed quantum computing journals
  • Expertise in quantum error correction and fault tolerance
  • Strong background in linear algebra and complex analysis
  • Experience with superconducting qubit architectures
  • Security clearance preferred for government contract work

Required Skills

Quantum Computing Qiskit Cirq Quantum Algorithms Quantum Error Correction Superconducting Qubits Linear Algebra Cryptography AI/ML Hybrid Models

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