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Information Technology 🏢 Full Time ⭐️ Verified

Quantum Computing Researcher

Nexus Labs
Austin
Estimated Salary
USD 160.000 – USD 220.000
Live Update
12 Mei 2026
Deadline
12 Mei 2027

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking a visionary researcher to develop next-gen quantum algorithms that will redefine computational boundaries. Our Austin-based innovation hub offers cutting-edge labs, collaborative workspaces, and unparalleled resources to transform theoretical concepts into real-world breakthroughs.

This role offers competitive compensation, equity participation, and the opportunity to shape the future of quantum technology. You'll work alongside Nobel laureates and industry pioneers in a culture that values intellectual curiosity and bold experimentation.

Responsibilities

  • Design and implement novel quantum algorithms for optimization problems
  • Develop error-correction protocols for scalable quantum systems
  • Lead cross-functional teams in prototyping quantum applications
  • Publish peer-reviewed research in top-tier scientific journals
  • Collaborate with hardware engineers to optimize quantum circuit designs
  • Identify emerging quantum threats and develop mitigation strategies
  • Secure external research funding through federal and industry partnerships

Qualifications

  • PhD in Quantum Computing, Physics, or Computer Science
  • 3+ years of hands-on quantum algorithm development experience
  • Proficiency in quantum programming frameworks (Qiskit, Cirq, etc.)
  • Deep understanding of quantum error correction techniques
  • Publication record in quantum information science
  • Experience with superconducting or ion-trap quantum systems
  • Strong analytical skills with complex mathematical modeling
  • US citizenship required for government contract compliance

Required Skills

Quantum Computing Algorithm Development Error Correction Qiskit Cirq Superconducting Qubits Ion Traps Mathematical Modeling Peer Review Federal Funding

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