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Quantum Computing Researcher

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 2026's quantum revolution! We're pioneering next-gen computational paradigms that will redefine global technology landscapes. As a Quantum Computing Researcher, you'll architect breakthrough algorithms in our state-of-the-art Austin facility, collaborating with Nobel laureates and industry disruptors. This isn't just a jobβ€”it's your chance to shape the fabric of tomorrow's digital universe.

We offer unparalleled R&D resources, flexible hybrid work arrangements, and equity participation in our moonshot projects. If you're ready to transcend classical computing boundaries and leave an indelible mark on human progress, we want you on our team.

Responsibilities

  • Design and implement novel quantum algorithms for complex optimization problems
  • Lead cross-functional teams in developing fault-tolerant quantum processors
  • Collaborate with AI specialists to create quantum-enhanced machine learning models
  • Secure patents for breakthrough quantum encryption methodologies
  • Publish high-impact research in peer-reviewed journals and industry whitepapers
  • Mentor junior researchers in quantum physics and computational theory
  • Partner with Fortune 500 clients to solve real-world quantum computing challenges

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field
  • 3+ years of hands-on quantum algorithm development experience
  • Proficiency in quantum programming languages (Q#, Qiskit, Cirq)
  • Deep understanding of quantum error correction techniques
  • Published research in top-tier quantum computing conferences
  • Expertise in tensor networks and quantum simulation frameworks
  • Strong background in linear algebra and probability theory
  • Experience with high-performance computing clusters

Required Skills

Quantum Computing Quantum Algorithms Qiskit Q# Fault Tolerance Quantum Cryptography Machine Learning Tensor Networks High-Performance Computing

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