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Quantum AI Research Scientist

Nexus Quantum Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Shape the future of artificial intelligence at Nexus Quantum Dynamics. We're pioneering quantum-AI convergence to solve humanity's greatest challenges by 2026. As a Quantum AI Research Scientist, you'll develop groundbreaking algorithms that leverage quantum supremacy to accelerate machine learning breakthroughs. Join our multidisciplinary team of Nobel laureates, Turing Award recipients, and industry disruptors in redefining what's computationally possible.

Your work will directly impact fields from drug discovery to climate modeling, using our proprietary quantum annealing hardware. We offer unparalleled resources—including a 512-qubit quantum processor—and a culture where curiosity drives innovation. If you're ready to push the boundaries of theoretical physics and applied AI, this is your moment.

Responsibilities

  • Design and implement novel quantum machine learning algorithms for NLP, computer vision, and optimization problems
  • Develop hybrid quantum-classical neural architectures leveraging 2026-era quantum hardware capabilities
  • Lead research initiatives in quantum error correction and fault-tolerant AI systems
  • Collaborate with hardware engineers to optimize quantum-AI integration on our proprietary quantum processors
  • Publish breakthrough research in Nature/Science journals and present at IEEE Quantum Week
  • Mentor postdoctoral researchers and cross-functional engineering teams
  • Secure $5M+ in DARPA/NSF grants for quantum-AI frontier projects

Qualifications

  • PhD in Quantum Computing, Theoretical Computer Science, or Physics with 3+ years of quantum-AI research
  • Expertise in quantum programming languages (Qiskit, Cirq, Q#) and quantum machine learning frameworks
  • Published work in top-tier quantum computing or AI conferences (QIP, NeurIPS, ICML)
  • Proficiency with high-performance computing (HPC) and distributed quantum systems
  • Deep understanding of quantum algorithms (Shor's, Grover's, VQE) and tensor networks
  • Experience with quantum hardware platforms (IBM Quantum, Rigetti, D-Wave)
  • Strong Python/C++ skills with expertise in PyTorch/TensorFlow for quantum-AI integration

Required Skills

Quantum Computing Machine Learning Python C++ Qiskit PyTorch Quantum Algorithms Quantum Hardware Theoretical Physics High-Performance Computing

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