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Quantum AI Research Scientist

Nexus Quantum Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
12 Mei 2026
Deadline
12 Mei 2027

Job Description

Join Nexus Quantum Technologies at the forefront of 2026's technological revolution! We're pioneering quantum-AI convergence for next-generation computational solutions. Our multidisciplinary team develops hybrid quantum-neural architectures to solve previously impossible optimization problems in cryptography, drug discovery, and climate modeling. Work alongside Nobel-caliber researchers in our state-of-the-art lab overlooking the Bay Bridge. We offer competitive equity packages, flexible hybrid work, and unparalleled professional development in this emerging field.

Responsibilities

  • Design and implement quantum machine learning algorithms for real-world applications
  • Collaborate with hardware engineers to optimize quantum circuit performance on superconducting processors
  • Develop hybrid quantum-classical neural networks for predictive analytics
  • Lead research publications in top-tier quantum computing journals
  • Translate theoretical quantum protocols into deployable enterprise solutions
  • Mentor junior researchers in quantum information theory
  • Secure patents for breakthrough quantum-AI methodologies

Qualifications

  • PhD in Quantum Computing, Physics, or Computer Science (or equivalent experience)
  • 3+ years experience with quantum programming languages (Q#, Qiskit, Cirq)
  • Published research in quantum machine learning or quantum algorithms
  • Proficiency in Python/C++ and high-performance computing frameworks
  • Deep understanding of quantum error correction and fault tolerance
  • Experience with quantum simulators (IBM Q, Rigetti Forest)
  • Strong background in linear algebra and complex probability theory
  • Proven track record of translating research to production systems

Required Skills

Quantum Computing Machine Learning Python C++ Qiskit Q# Superconducting Qubits Neural Networks Cryptography High-Performance Computing

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