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Quantum Computing Research Scientist

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 quantum revolution as we pioneer the next generation of computing for 2026. We seek a brilliant Quantum Computing Research Scientist to develop breakthrough algorithms and architectures that will redefine technological boundaries. This role offers unparalleled opportunities to shape the future of cryptography, AI, and materials science.

As part of our elite R&D division, you'll collaborate with Nobel laureates and industry pioneers in state-of-the-art facilities. We offer competitive compensation, flexible work arrangements, and resources to publish groundbreaking research. Your work will directly impact how humanity solves previously unsolvable problems.

Responsibilities

  • Design and implement novel quantum algorithms for complex optimization problems
  • Develop error correction protocols for fault-tolerant quantum systems
  • Lead cross-functional research teams on quantum hardware-software integration
  • Publish high-impact research in peer-reviewed journals and conferences
  • Collaborate with government and industry partners on quantum security initiatives
  • Patent breakthrough quantum computing methodologies and architectures
  • Mentor junior researchers and drive innovation in quantum machine learning

Qualifications

  • PhD in Physics, Computer Science, or related quantum field with 5+ years experience
  • Proven expertise in quantum circuit design and quantum information theory
  • Publication record in Nature/Science or equivalent tier journals
  • Proficiency with quantum programming frameworks (Qiskit, Cirq, Q#)
  • Deep understanding of quantum decoherence and error mitigation techniques
  • Experience with superconducting or photonic quantum systems
  • Demonstrated ability to secure competitive research funding

Required Skills

Quantum Computing Quantum Algorithms Error Correction Qiskit Cryptography Machine Learning Superconducting Systems

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