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Quantum AI Research Scientist

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

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer the next wave of AI-driven quantum systems. We're seeking a visionary Quantum AI Research Scientist to develop groundbreaking algorithms that will redefine computing by 2026. This role offers unparalleled opportunities to shape the future of artificial intelligence while collaborating with Nobel laureates and industry disruptors in our state-of-the-art San Francisco facility.

Nexus Labs provides a dynamic environment where your innovations will directly impact global industries. We offer competitive equity packages, flexible work arrangements, and dedicated R&D budgets for cutting-edge projects. Your work will accelerate humanity's transition into the quantum era.

Responsibilities

  • Design and implement quantum machine learning algorithms for next-gen computational models
  • Lead cross-functional research teams in developing AI-quantum hybrid systems
  • Collaborate with hardware engineers to optimize quantum-AI integration protocols
  • Publish breakthrough research in top-tier journals and industry conferences
  • Secure external funding through NSF and DARPA grants
  • Mentor junior researchers in quantum computing principles
  • Develop patentable technologies for commercial applications

Qualifications

  • PhD in Quantum Computing, AI, or Physics with 5+ years research experience
  • Expertise in quantum algorithms and machine learning frameworks
  • Published work in Nature/Science or equivalent tier journals
  • Proficiency with quantum programming languages (Qiskit, Cirq) and AI toolkits
  • Strong background in complex mathematical modeling
  • Experience with high-performance computing environments
  • Track record of translating research into commercial applications

Required Skills

Quantum Computing Machine Learning AI Research Quantum Algorithms Cirq Qiskit High-Performance Computing Mathematical Modeling R&D Scientific Publishing

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