Job Description
Join NeuroQuantum Dynamics at the forefront of 2026's technological revolution. We're pioneering quantum-AI convergence to solve humanity's most complex challenges. As a Quantum AI Research Scientist, you'll architect next-generation neural networks operating on quantum substrates, pushing beyond classical computing limits. Our Austin R&D hub offers cutting-edge labs, flexible hybrid work, and unparalleled resources to transform theoretical breakthroughs into real-world solutions.
Shape the future of machine learning, contribute to breakthrough publications in Nature Quantum, and collaborate with Nobel laureates in our mission to democratize quantum computing. We value audacious thinkers who thrive at the intersection of physics, computer science, and AI.
Responsibilities
- Design quantum neural network architectures for exponential speedup in deep learning tasks
- Develop error-corrected quantum algorithms for unsupervised learning and generative modeling
- Lead cross-functional teams in prototyping quantum-AI hybrid systems
- Translate theoretical quantum computing models into practical ML frameworks
- Drive innovation in quantum-enhanced natural language processing
- Publish high-impact research in top-tier quantum/AI conferences
- Mentor junior researchers in quantum machine learning methodologies
Qualifications
- PhD in Quantum Computing, Machine Learning, or Computational Physics
- Expertise in quantum circuit design and quantum error correction
- Proficiency in quantum programming frameworks (Qiskit, Cirq, PennyLane)
- Published research in quantum machine learning or quantum neural networks
- Strong Python/C++ skills with experience in TensorFlow/PyTorch
- Deep understanding of quantum information theory and entanglement protocols
- Experience with high-performance computing and distributed quantum systems