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2026 Quantum AI Research Lead

Nexus Dynamics
Austin
Estimated Salary
USD 180.000 – USD 280.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Join Nexus Dynamics at the forefront of technological evolution. We're seeking a visionary 2026 Quantum AI Research Lead to architect the next paradigm of computational intelligence. This role bridges quantum computing and artificial intelligence to solve humanity's most complex challenges. You'll lead a cross-disciplinary team pioneering breakthrough algorithms, develop scalable quantum machine learning frameworks, and collaborate with global research institutions to define the future of autonomous systems.

What you'll achieve: Design quantum-resistant AI architectures, publish seminal research in Nature/Science journals, and mentor the next generation of quantum innovators. Our Austin campus features state-of-the-art quantum labs and a culture of relentless innovation.

Responsibilities

  • Architect quantum AI frameworks for real-world applications in finance, healthcare, and logistics
  • Lead cross-functional teams of quantum physicists and ML engineers
  • Develop error-corrected quantum algorithms for unsupervised learning
  • Secure $5M+ in research grants from NSF, DARPA, and industry partners
  • Establish industry standards for quantum-ML integration protocols
  • Publish top-tier research and speak at global tech conferences
  • Mentor PhD candidates and postdoctoral researchers

Qualifications

  • PhD in Quantum Computing, Machine Learning, or related field
  • 5+ years of research leadership in quantum/AI domains
  • Published work in Nature/Science/Science Advances
  • Expertise in Qiskit, Cirq, and quantum error correction
  • Strong background in tensor networks and variational quantum circuits
  • Track record of securing federal research funding
  • Experience with high-performance computing clusters
  • Proficiency in Python, TensorFlow, and quantum simulators

Required Skills

Quantum Computing Machine Learning AI Research Qiskit TensorFlow Quantum Error Correction Tensor Networks High-Performance Computing Scientific Research

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