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Quantum Computing Research Scientist 2026

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

Job Description

Join Nexus Future Labs at the forefront of technological revolution as we pioneer quantum computing applications for 2026. This role demands a visionary scientist to develop next-gen quantum algorithms and hybrid classical-quantum systems that will redefine computational boundaries. You'll collaborate with Nobel laureates and industry disruptors in our state-of-the-art facility overlooking the San Francisco Bay.

We offer competitive equity packages, flexible work arrangements, and unparalleled resources to accelerate your research. Our team has already achieved breakthroughs in quantum error correction and are now targeting practical quantum supremacy by 2026.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and machine learning applications
  • Lead cross-functional teams to develop hybrid quantum-classical computing frameworks
  • Publish groundbreaking research in top-tier journals and conferences
  • Secure federal and private research grants targeting 2026 quantum milestones
  • Mentor junior researchers and develop quantum curriculum for next-gen talent
  • Collaborate with hardware teams to bridge theoretical models with practical quantum processors

Qualifications

  • PhD in Physics, Computer Science, or related field with quantum computing focus
  • 3+ years of hands-on experience with quantum programming frameworks (Qiskit, Cirq)
  • Published research in quantum algorithms or quantum information theory
  • Expertise in high-performance computing and parallel processing architectures
  • Demonstrated ability to secure research funding (NSF, DOE, or corporate grants)
  • Strong background in machine learning and optimization theory
  • Experience with quantum error correction and fault-tolerant systems

Required Skills

Quantum Computing Qiskit Cirq Machine Learning Algorithm Design High-Performance Computing Research Fault-Tolerant Systems

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