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Information Technology 🏢 Full Time ⭐️ Verified

Quantum Computing Researcher

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

Job Description

Join Nexus Labs at the forefront of technological innovation as we pioneer quantum computing solutions that will redefine industries by 2026. We're seeking a visionary Quantum Computing Researcher to develop next-generation algorithms and protocols that will power the next era of computational breakthroughs. Work in our state-of-the-art Austin facility alongside Nobel Prize-winning scientists and industry disruptors. This role offers unparalleled opportunities to shape the future of technology while enjoying comprehensive benefits, flexible work arrangements, and a competitive compensation package.

Responsibilities

  • Design and implement novel quantum algorithms for complex computational problems
  • Lead research initiatives in quantum error correction and fault-tolerant systems
  • Collaborate with hardware engineers to optimize quantum processor architectures
  • Develop cryptographic protocols for post-quantum security frameworks
  • Publish groundbreaking research in leading scientific journals
  • Secure research grants and partnerships with academic institutions
  • Mentor junior researchers and contribute to intellectual property development

Qualifications

  • PhD in Quantum Computing, Physics, or related field (or equivalent experience)
  • 3+ years of hands-on quantum algorithm development experience
  • Expertise in quantum programming languages (Qiskit, Cirq, or Q#)
  • Strong publication record in quantum information science
  • Proficiency in linear algebra, probability theory, and complex analysis
  • Experience with quantum simulation frameworks and hardware interfaces
  • Proven ability to secure competitive research funding
  • Track record of interdisciplinary collaboration

Required Skills

Quantum Computing Algorithm Development Cryptography Quantum Programming Research Methodology Machine Learning Data Analysis Scientific Publishing

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