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Quantum AI Research Scientist - 2026 Vision

Nexus Future Labs
Austin
Estimated Salary
USD 180.000 – USD 280.000
Live Update
23 Mei 2026
Deadline
23 Mei 2027

Job Description

Join Nexus Future Labs at the forefront of 2026's technological revolution as we pioneer the convergence of quantum computing and artificial intelligence. Our Austin-based research center is seeking visionary Quantum AI Research Scientists to develop next-generation algorithms that will redefine computational boundaries. You'll collaborate with Nobel laureates and industry disruptors in an environment where theoretical physics meets practical application, contributing to breakthroughs in drug discovery, climate modeling, and autonomous systems.

We offer competitive equity packages, unlimited R&D budgets, and access to our 500-qubit quantum annealer. This role is part of our 'Project Helios' initiative to create the world's first commercially viable quantum neural network by 2026.

Responsibilities

  • Design and implement hybrid quantum-classical machine learning frameworks for complex optimization problems
  • Lead cross-functional teams in prototyping quantum algorithms for real-world applications
  • Publish groundbreaking research in top-tier journals and industry conferences
  • Collaborate with hardware engineers to co-design quantum processors optimized for AI workloads
  • Develop security protocols for quantum-resistant AI systems
  • Mentor junior researchers in quantum machine learning methodologies
  • Secure external funding through NSF grants and industry partnerships

Qualifications

  • PhD in Quantum Computing, Theoretical Physics, or AI with 3+ years industry experience
  • Expertise in quantum algorithms (Shor's, Grover's, VQE) and quantum error correction
  • Proficiency in quantum programming languages (Qiskit, Cirq, Q#) and AI frameworks
  • Published research in Nature/Science or equivalent tier journals
  • Experience with NISQ-era hardware constraints and mitigation strategies
  • Strong background in deep learning architectures and tensor networks
  • Ability to translate complex quantum concepts into practical business applications

Required Skills

Quantum Computing Machine Learning AI Research Quantum Algorithms Qiskit Python Cirq Theoretical Physics Deep Learning Quantum Error Correction Tensor Networks

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