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Quantum Computing Research Lead

Nexus Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
19 Mei 2026
Deadline
19 Mei 2027

Job Description

Join Nexus Labs at the forefront of technological revolution as we pioneer quantum computing breakthroughs for 2026 and beyond. We're seeking a visionary Quantum Computing Research Lead to architect next-gen systems that will redefine computational boundaries. This role demands a blend of deep technical expertise and strategic foresight to transform theoretical possibilities into real-world applications.

As a key member of our Innovation Division, you'll collaborate with Nobel laureates and industry disruptors in a state-of-the-art facility. We offer unparalleled resources, including access to quantum annealing hardware and $50M in annual R&D funding. Your work will directly impact fields from climate modeling to drug discovery, positioning Nexus Labs as the global leader in quantum commercialization.

Responsibilities

  • Design and implement scalable quantum algorithms for practical 2026-era applications
  • Lead a multidisciplinary team of physicists, engineers, and AI specialists
  • Develop error-correction frameworks for fault-tolerant quantum systems
  • Establish strategic partnerships with quantum hardware manufacturers
  • Secure $10M+ in government and industry grants for quantum research
  • Publish breakthrough findings in Nature/Science journals
  • Architect hybrid quantum-classical computing architectures

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field
  • 5+ years of hands-on quantum algorithm development experience
  • Proven track record of publishing in top-tier scientific journals
  • Expertise in quantum error correction and fault tolerance
  • Strong background in machine learning for quantum systems
  • Experience securing federal research grants ($5M+ preferred)
  • Leadership of cross-disciplinary technical teams (10+ members)

Required Skills

Quantum Computing Quantum Algorithms Error Correction Machine Learning Scientific Research Grant Writing Team Leadership Hybrid Computing

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