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Quantum Computing Research Scientist

Nexus Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

Join Nexus Labs at the forefront of technological innovation as we pioneer breakthroughs in quantum computing for 2026 and beyond. We're seeking a visionary Quantum Computing Research Scientist to develop next-gen algorithms and solve complex computational challenges that will redefine industries. Our Austin-based team collaborates with NASA, IBM, and MIT to push the boundaries of quantum supremacy.

What you'll achieve: Design scalable quantum circuits, optimize error-correction protocols, and publish research in top-tier journals. You'll work in our state-of-the-art cryogenic lab and contribute to projects that could revolutionize cryptography, drug discovery, and artificial intelligence.

Responsibilities

  • Develop and implement novel quantum algorithms for optimization and machine learning
  • Design fault-tolerant quantum architectures using superconducting qubits
  • Collaborate with hardware engineers to bridge theoretical models with physical implementations
  • Lead cross-functional research initiatives with government and industry partners
  • Publish peer-reviewed papers and present findings at global conferences
  • Mentor junior researchers and drive innovation in quantum software development

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field (or equivalent experience)
  • 3+ years of hands-on quantum algorithm development
  • Proficiency in quantum programming languages (Q#, Qiskit, Cirq)
  • Deep understanding of quantum error correction and decoherence mitigation
  • Publication record in Nature/Science or equivalent tier journals
  • Experience with high-performance computing and parallel processing
  • Strong analytical skills with ability to translate complex concepts into practical solutions

Required Skills

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

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