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Quantum Computing Research Scientist

Nexus Labs
Austin
Estimated Salary
USD 150.000 – USD 220.000
Live Update
25 Mei 2026
Deadline
25 Mei 2027

Job Description

Join Nexus Labs at the forefront of technological revolution as we pioneer quantum computing solutions that will redefine 2026 and beyond. Our Austin-based innovation hub is seeking visionary Quantum Computing Research Scientists to develop next-generation algorithms and hardware architectures. You'll collaborate with Nobel laureates and industry disruptors to solve previously impossible computational challenges in cryptography, material science, and AI optimization. We offer unparalleled resources, a culture of intellectual curiosity, and the opportunity to shape humanity's technological future.

Responsibilities

  • Design and implement novel quantum algorithms for practical 2026-era applications
  • Lead experimental research on quantum error correction and fault-tolerant systems
  • Develop hybrid quantum-classical computing frameworks for enterprise solutions
  • Collaborate with hardware teams to optimize qubit architectures and coherence times
  • Publish breakthrough research in leading scientific journals and industry whitepapers
  • Mentor junior researchers and drive quantum literacy initiatives across the organization

Qualifications

  • PhD in Quantum Computing, Physics, Computer Science, or related field
  • 3+ years of hands-on experience with quantum programming (Qiskit, Cirq, or Q#)
  • Expertise in quantum error correction and fault-tolerant computing principles
  • Publication record in top-tier quantum computing conferences (QIP, APS March Meeting)
  • Strong background in linear algebra, probability theory, and computational complexity
  • Demonstrated ability to translate theoretical concepts into experimental prototypes
  • Experience with high-performance computing environments and parallel processing

Required Skills

Quantum Computing Qiskit Cirq Quantum Error Correction Fault-Tolerant Systems Algorithm Design High-Performance Computing Linear Algebra

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