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Quantum AI Research Scientist

Nexus Quantum Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
4 Juni 2026
Deadline
4 Jun 2027

Job Description

Join Nexus Quantum Dynamics at the forefront of 2026's technological revolution. We're pioneering quantum-AI hybrid systems that will redefine computational boundaries. As a Quantum AI Research Scientist, you'll architect next-generation algorithms, collaborate with Nobel Prize-winning physicists, and contribute to breakthroughs that will shape humanity's digital future. Our state-of-the-art lab in San Francisco offers unparalleled resources for experimentation and innovation.

We offer competitive equity packages, flexible hybrid work arrangements, and exclusive access to industry-defining conferences. This is your opportunity to work on problems that don't exist yet – problems that will define the next decade of human progress.

Responsibilities

  • Design and implement quantum neural networks for unsupervised learning tasks
  • Develop novel error-correction protocols for quantum-AI hybrid systems
  • Lead experimental validation of quantum supremacy claims in machine learning
  • Collaborate with hardware teams to optimize quantum-AI co-design architectures
  • Author peer-reviewed publications in Nature/Science journals
  • Mentor PhD candidates in quantum machine learning methodologies
  • Secure $1M+ in annual research grants from DARPA/NSF

Qualifications

  • PhD in Quantum Computing, Physics, or AI from Tier-1 institution
  • 3+ years of hands-on quantum algorithm development (Qiskit/Cirq)
  • Published work in top-tier quantum/AI conferences (QIP, NeurIPS)
  • Expertise in tensor networks and quantum information theory
  • Proficiency in Python, C++, and quantum simulation frameworks
  • Demonstrated ability to translate theoretical models into hardware implementations
  • Security clearance eligibility (preferred)

Required Skills

Quantum Computing Machine Learning Python Qiskit Cirq Tensor Networks Quantum Information Theory Research

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