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Quantum Computing Research Scientist

Nexus Future Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

Join Nexus Future Labs at the forefront of technological revolution as we pioneer quantum computing solutions that will redefine industries by 2026. Our Austin-based research hub combines cutting-edge hardware development with algorithmic innovation to solve previously impossible computational challenges. This role offers unparalleled opportunities to shape the next generation of quantum technologies while collaborating with Nobel laureates and industry disruptors.

We offer competitive equity packages, flexible hybrid work arrangements, and access to state-of-the-art quantum annealing systems. Our team operates in a startup environment backed by institutional funding, ensuring resources match ambition. Relocation assistance available for exceptional candidates.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and simulation problems
  • Develop error mitigation protocols for NISQ-era quantum processors
  • Lead cross-functional teams in translating theoretical models into practical applications
  • Publish peer-reviewed research in top-tier quantum computing journals
  • Collaborate with hardware teams to co-design quantum system architectures
  • Secure external funding through NSF grants and industry partnerships

Qualifications

  • PhD in Quantum Computing, Physics, or Computer Science (or equivalent experience)
  • 3+ years of hands-on quantum algorithm development experience
  • Proficiency in quantum programming languages (Qiskit, Cirq, or Q#)
  • Publication record in quantum computing or related fields
  • Deep understanding of quantum error correction and fault tolerance
  • Experience with quantum hardware platforms (IBM Quantum, Rigetti, or IonQ)
  • Strong background in linear algebra and complex analysis

Required Skills

Quantum Computing Qiskit Cirq Quantum Algorithms Quantum Error Correction NISQ Machine Learning Python Linear Algebra Fault Tolerance

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