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Quantum Computing Research Scientist

Nexus Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
New
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. As a Quantum Computing Research Scientist, you'll drive breakthroughs in quantum algorithms, error correction, and hardware optimization. Our Austin-based innovation hub offers unparalleled resources and collaborative freedom to transform theoretical possibilities into real-world applications.

We're seeking visionaries who thrive at the intersection of physics, computer science, and artificial intelligence. Your work will directly impact industries from pharmaceuticals to logistics, solving problems once deemed unsolvable. Join a team where curiosity is valued and failure is merely data on the path to discovery.

Responsibilities

  • Design and implement novel quantum algorithms for practical applications
  • Lead quantum error correction protocol development
  • Collaborate with hardware engineers on quantum processor optimization
  • Develop quantum machine learning frameworks for 2026-era data challenges
  • Publish cutting-edge research in peer-reviewed journals
  • Mentor junior researchers and foster cross-disciplinary innovation
  • Secure external funding through NSF and DoE grants

Qualifications

  • PhD in Physics, Computer Science, or related field with quantum focus
  • 3+ years of hands-on quantum algorithm development experience
  • Proficiency in quantum programming languages (Q#, Qiskit, Cirq)
  • Deep understanding of quantum error correction techniques
  • Publication record in quantum computing research
  • Experience with quantum hardware integration (IBM, Rigetti, IonQ)
  • Strong background in linear algebra and quantum mechanics
  • Ability to translate complex concepts for technical and non-technical audiences

Required Skills

Quantum Computing Quantum Algorithms Error Correction Qiskit Cirq Q# Machine Learning Physics Research

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