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Quantum Computing Research Scientist

Nexus Quantum Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Join Nexus Quantum Labs at the forefront of technological revolution! We're pioneering quantum computing solutions that will redefine industries by 2026. As a Research Scientist, you'll develop next-gen quantum algorithms, collaborate with Nobel laureates, and shape the future of computational science. Our Austin campus features state-of-the-art labs, unlimited resources, and a culture of relentless innovation.

We offer competitive equity, flexible hybrid work, and sabbatical programs for groundbreaking discoveries. If you're passionate about solving humanity's greatest challenges through quantum mechanics, this is your moment.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and cryptography
  • Lead experimental validation of quantum supremacy protocols on superconducting qubits
  • Collaborate with AI teams to develop hybrid quantum-classical machine learning models
  • Publish breakthrough research in top-tier journals and present at global conferences
  • Mentor junior researchers in quantum error correction techniques
  • Secure patents for proprietary quantum hardware innovations
  • Partner with industry leaders to commercialize quantum applications

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field (or equivalent experience)
  • 3+ years of hands-on quantum computing research with published papers
  • Expertise in quantum programming languages (Q#, Qiskit, Cirq)
  • Proficiency with quantum circuit optimization and error correction
  • Strong background in linear algebra and complex systems theory
  • Experience with superconducting qubit systems or trapped-ion architectures
  • Demonstrated ability to translate theoretical concepts into experimental prototypes

Required Skills

Quantum Computing Quantum Algorithms Superconducting Qubits Qiskit Q# Error Correction Machine Learning Cryptography

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