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Quantum AI Research Scientist

Nexus Quantum Labs
Austin
Estimated Salary
USD 180.000 – USD 280.000
Live Update
20 Mei 2026
Deadline
20 Mei 2027

Job Description

Join the forefront of technological evolution at Nexus Quantum Labs, where we're pioneering the fusion of quantum computing and artificial intelligence to solve humanity's grandest challenges. As a Quantum AI Research Scientist, you'll architect breakthrough algorithms and computational frameworks that redefine what's possible in 2026 and beyond. Our Austin hub offers state-of-the-art facilities and a collaborative culture where your expertise will directly shape the future of computational science.

We're seeking visionary minds to develop hybrid quantum-classical models, optimize error-correction protocols, and create novel machine learning architectures for quantum processors. If you thrive at the intersection of theoretical physics and applied AI, this is your opportunity to leave an indelible mark on technological history.

Responsibilities

  • Design and implement quantum machine learning algorithms leveraging QML frameworks
  • Develop novel error-correction techniques for fault-tolerant quantum systems
  • Create hybrid quantum-classical neural networks for optimization problems
  • Lead cross-functional teams in prototyping quantum AI applications
  • Author peer-reviewed research and present findings at international conferences
  • Collaborate with hardware engineers to optimize quantum algorithm performance
  • Secure and manage high-performance computing resources for quantum simulations

Qualifications

  • PhD in Quantum Computing, Physics, Computer Science, or related field
  • 3+ years of experience in quantum algorithm development or QML research
  • Proficiency with quantum programming languages (Qiskit, Cirq, or Q#)
  • Deep understanding of quantum error correction and fault tolerance
  • Published research in quantum computing or AI at top-tier conferences
  • Expertise in Python, TensorFlow/PyTorch, and high-performance computing
  • Strong background in linear algebra, probability, and information theory
  • Experience with quantum hardware platforms (IBM Q, Rigetti, or IonQ)

Required Skills

Quantum Computing Machine Learning Qiskit Cirq TensorFlow Python Error Correction Fault Tolerance QML Neural Networks

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