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Quantum AI Research Scientist

Nexus Future Labs
Austin
Estimated Salary
USD 150.000 – USD 220.000
New
Live Update
18 Mei 2026
Deadline
18 Mei 2027

Job Description

Join Nexus Future Labs at the forefront of technological evolution as we pioneer the next generation of quantum-AI hybrid systems. We seek a visionary Quantum AI Research Scientist to develop groundbreaking algorithms that will redefine computational boundaries by 2026. You'll collaborate with Nobel laureates and lead projects in quantum machine learning, neural network optimization, and autonomous system design. This role offers unparalleled resources to transform theoretical concepts into real-world applications that will shape humanity's technological trajectory.

Responsibilities

  • Design and implement quantum machine learning algorithms for 2026-era computational challenges
  • Lead cross-functional teams in developing hybrid quantum-classical neural networks
  • Research and optimize quantum-resistant cryptography protocols for future security infrastructure
  • Develop simulation frameworks for quantum-AI system behavior in high-stakes environments
  • Author breakthrough publications in top-tier journals and present at global tech summits
  • Collaborate with hardware engineers to co-design next-generation quantum processors
  • Establish ethical frameworks for quantum-AI deployment in critical systems

Qualifications

  • PhD in Quantum Computing, Computer Science, or related field with 5+ years research experience
  • Published research in quantum machine learning or quantum information theory
  • Expertise in quantum circuit design and quantum error correction methodologies
  • Proficiency in Python, Qiskit, and quantum simulation frameworks
  • Demonstrated experience with large-scale distributed computing systems
  • Strong background in theoretical physics and advanced mathematics
  • Proven track record of translating complex research into commercial applications

Required Skills

Quantum Computing Machine Learning Python Qiskit Cryptography Neural Networks Distributed Systems Theoretical Physics

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