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Quantum AI Research Scientist

NeuroTech Labs
San Francisco
Estimated Salary
USD 190.000 – USD 280.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Join NeuroTech Labs at the forefront of 2026's technological revolution! We're seeking a visionary Quantum AI Research Scientist to pioneer breakthroughs at the intersection of quantum computing and artificial intelligence. Shape the future of computational intelligence while working in our state-of-the-art San Francisco facility with cutting-edge resources and unparalleled collaborative opportunities.

About NeuroTech Labs: We're a preeminent research institute dedicated to developing quantum-optimized AI systems that will redefine industries by 2026. Our team includes Nobel laureates and Turing Award winners pushing the boundaries of what's computationally possible.

What We Offer: Competitive equity packages, unlimited research budget, flexible hybrid work, and the chance to publish in Nature/Science journals. Work directly with quantum hardware pioneers while mentoring the next generation of quantum AI researchers.

Responsibilities

  • Design and implement novel quantum neural network architectures for 2026-era computational challenges
  • Lead cross-disciplinary research teams in quantum machine learning optimization
  • Develop error-correction protocols for quantum AI systems at scale
  • Pioneer hybrid quantum-classical algorithms for real-world industrial applications
  • Collaborate with hardware teams to co-design quantum processors optimized for AI workloads
  • Author peer-reviewed publications and secure NSF/NASA research grants
  • Establish ethical frameworks for quantum AI deployment in regulated industries

Qualifications

  • PhD in Quantum Computing, Machine Learning, or Computational Physics (post-doc preferred)
  • 5+ years of research experience in quantum algorithms or deep neural networks
  • Published work in top-tier journals (Nature, Science, IEEE TPAMI)
  • Proficiency with Qiskit, Cirq, or equivalent quantum programming frameworks
  • Expertise in tensor networks and quantum error correction methodologies
  • Demonstrated ability to secure $1M+ in research funding
  • Strong background in high-performance computing and parallel processing

Required Skills

Quantum Computing Machine Learning Neural Networks Qiskit Cirq Tensor Networks Research High-Performance Computing Quantum Error Correction

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