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Quantum AI Research Scientist

Nexus Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Join Nexus Labs 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-gen computational frameworks that transcend classical limitations. Our multidisciplinary team operates at the intersection of quantum physics, machine learning, and emergent computing paradigms. This role offers unparalleled resources—including our 512-qubit quantum annealer—and the opportunity to publish groundbreaking research in top-tier journals.

We foster a culture of radical innovation where curiosity is our compass. Enjoy flexible schedules, unlimited R&D budgets, and quarterly innovation retreats to global tech hubs. Your work will directly influence the trajectory of AI development in the coming decade.

Responsibilities

  • Design and implement hybrid quantum-classical algorithms for unsupervised learning
  • Develop error-correction protocols for fault-tolerant quantum neural networks
  • Lead cross-functional teams in prototyping quantum-AI applications for drug discovery and materials science
  • Author peer-reviewed publications and secure federal grants for quantum computing initiatives
  • Optimize quantum circuit architectures for real-time inference at scale
  • Mentor junior researchers in quantum machine learning methodologies
  • Collaborate with hardware teams to co-design quantum processors optimized for AI workloads

Qualifications

  • PhD in Quantum Computing, Machine Learning, or Computational Physics (or equivalent experience)
  • 5+ years of research experience in quantum algorithms or quantum machine learning
  • Proficiency in quantum programming languages (Qiskit, Cirq, or Q#)
  • Publication record in Nature/Science or top-tier ML conferences (NeurIPS, ICML)
  • Expertise in tensor networks and quantum state tomography
  • Strong background in deep learning frameworks (PyTorch/TensorFlow)
  • Experience with high-performance computing clusters and GPU acceleration
  • Demonstrated ability to translate theoretical concepts into experimental prototypes

Required Skills

Quantum Computing Machine Learning Python Qiskit TensorFlow PyTorch High-Performance Computing Quantum Algorithms AI Research

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