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Quantum AI Research Scientist

Nexus Dynamics
Austin
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
19 Mei 2026
Deadline
19 Mei 2027

Job Description

Join Nexus Dynamics at the forefront of technological evolution as we pioneer breakthroughs in quantum computing and artificial intelligence. We're seeking a visionary Quantum AI Research Scientist to architect solutions that will redefine industries by 2026. In this role, you'll collaborate with Nobel laureates and industry disruptors to develop proprietary algorithms, optimize quantum machine learning models, and commercialize next-gen technologies. Our Austin headquarters features a state-of-the-art quantum lab and offers competitive benefits including equity, flexible work arrangements, and professional development stipends. Be part of the team shaping humanity's technological future.

Responsibilities

  • Design and implement quantum machine learning algorithms for real-world applications
  • Lead R&D projects in quantum-resistant cryptography and AI optimization
  • Collaborate with hardware engineers to develop quantum-classical hybrid systems
  • Publish research in top-tier journals and present at international conferences
  • Secure federal and private research grants ($1M+ target annually)
  • Mentor junior researchers and develop intellectual property portfolios

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field with 5+ years research experience
  • Expertise in quantum machine learning frameworks (Qiskit, Cirq, PennyLane)
  • Publication record in Nature/Science or equivalent tier journals
  • Proficiency in high-performance computing environments (HPC, GPU clusters)
  • Strong background in AI/ML (TensorFlow, PyTorch) and quantum error correction
  • Track record of securing research funding or commercializing IP
  • Excellent written/verbal communication skills with cross-functional teams

Required Skills

Quantum Computing Machine Learning Cryptography High-Performance Computing Python TensorFlow Qiskit Research Methodology

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