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Quantum Computing Researcher

Nexus Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Join Nexus Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking visionary researchers to develop next-gen quantum algorithms that will redefine computational boundaries. Our Austin hub combines cutting-edge infrastructure with collaborative innovation spaces, offering unparalleled resources to transform theoretical concepts into breakthrough applications.

As part of our interdisciplinary team, you'll work alongside Nobel laureates and industry pioneers to solve humanity's most complex challenges. We offer competitive equity packages, flexible hybrid work arrangements, and dedicated R&D funding for your experimental projects.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and simulation problems
  • Lead experimental validation of quantum circuits on superconducting and photonic platforms
  • Collaborate with AI teams to develop hybrid quantum-classical machine learning frameworks
  • Publish breakthrough research in top-tier journals and present at international conferences
  • Secure external funding through NSF and DOE grant applications
  • Mentor junior researchers and contribute to patent development

Qualifications

  • PhD in Physics, Computer Science, or related field with quantum specialization
  • 3+ years hands-on experience with quantum programming languages (Qiskit, Cirq, or Quipper)
  • Published research in quantum error correction or fault-tolerant architectures
  • Proficiency in quantum hardware platforms (IBM Q, Rigetti, or IonQ)
  • Demonstrated expertise in high-performance computing environments
  • Strong track record of interdisciplinary collaboration
  • US citizenship or permanent residency required for government contract work

Required Skills

Quantum Computing Qiskit Cirq Superconducting Qubits Quantum Error Correction Machine Learning High-Performance Computing Theoretical Physics

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