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Quantum AI Research Scientist

Nexus Quantum Labs
Austin
Estimated Salary
USD 180.000 – USD 280.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Join the forefront of technological innovation at Nexus Quantum Labs, where we're pioneering the convergence of quantum computing and artificial intelligence to solve humanity's greatest challenges. As a Quantum AI Research Scientist, you'll architect next-gen algorithms that leverage quantum entanglement for exponential computational breakthroughs. Our Austin-based hub offers unparalleled resources—including a 128-qubit quantum processor and a $50M R&D budget—to push the boundaries of what's possible. Collaborate with Nobel laureates and disrupt industries from drug discovery to climate modeling while shaping the quantum revolution of 2026.

Responsibilities

  • Design and implement hybrid quantum-classical machine learning frameworks for complex optimization problems
  • Develop novel quantum error-correction protocols for fault-tolerant AI systems
  • Create quantum neural networks demonstrating superposition advantages over classical architectures
  • Lead cross-functional teams in prototyping quantum-secured AI applications for enterprise clients
  • Author breakthrough research published in Nature Quantum and IEEE journals
  • Secure $1M+ in quantum computing grants through NIH and NSF partnerships

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field with 5+ years of quantum algorithm development
  • Expertise in quantum programming languages (Q#, Qiskit, Cirq) and circuit optimization
  • Proven track record of publishing top-tier quantum machine learning research
  • Deep understanding of tensor networks and quantum information theory
  • Proficiency in high-performance computing environments (HPC, quantum simulators)
  • Experience with quantum hardware integration (IBM Q, Rigetti, IonQ)
  • Strong background in AI/ML frameworks (PyTorch, TensorFlow) with quantum extensions

Required Skills

Quantum Computing Machine Learning Q# Python C++ Quantum Algorithms AI Research HPC Tensor Networks

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