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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 Quantum Computing Research Scientist, you'll develop groundbreaking algorithms and protocols to solve previously impossible computational challenges. Collaborate with world-class physicists and engineers in our state-of-the-art Austin facility to accelerate quantum supremacy applications in cryptography, drug discovery, and climate modeling.

Responsibilities

  • Design and implement quantum algorithms for complex optimization and simulation problems
  • Conduct cutting-edge research in quantum error correction and fault-tolerant systems
  • Develop novel quantum software frameworks compatible with next-generation hardware
  • Lead cross-functional teams to prototype quantum applications in finance and logistics
  • Publish breakthrough research in peer-reviewed journals and industry conferences
  • Secure external funding through government grants and corporate partnerships
  • Mentor junior researchers and foster innovation within the quantum ecosystem

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field (or equivalent experience)
  • 5+ years of hands-on experience with quantum computing frameworks (Qiskit, Cirq, etc.)
  • Expertise in quantum algorithms, quantum machine learning, and cryptography
  • Proven track record of publishing high-impact quantum research
  • Strong programming skills in Python, C++, and quantum assembly languages
  • Experience with quantum hardware platforms (IBM Q, Rigetti, etc.)
  • Demonstrated ability to secure research funding and manage complex projects
  • Preferred: Background in industry applications (finance, pharmaceuticals, AI)

Required Skills

Quantum Computing Quantum Algorithms Quantum Cryptography Qiskit Cirq Python Quantum Hardware Machine Learning Research Methodology

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