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Quantum Computing Researcher 2026

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 quantum computing revolution. We're pioneering the next generation of quantum systems that will redefine technology by 2026. As a Quantum Computing Researcher, you'll work in our state-of-the-art Austin lab, collaborating with Nobel laureates and industry pioneers to develop breakthrough algorithms and hardware solutions. Our hybrid-first culture offers flexibility while ensuring deep collaboration in our quantum research clusters. Benefit from cutting-edge resources, competitive compensation, and opportunities to shape the future of computational science.

Responsibilities

  • Design and implement quantum algorithms for optimization and simulation problems
  • Develop error-correction protocols for fault-tolerant quantum systems
  • Collaborate with hardware engineers to optimize quantum processor architectures
  • Lead research initiatives targeting 2026 quantum computing milestones
  • Publish findings in peer-reviewed journals and present at international conferences
  • Mentor junior researchers in quantum computing methodologies
  • Secure and manage quantum research grants from government and private entities

Qualifications

  • PhD in Quantum Computing, Physics, Computer Science, or related field
  • 3+ years of hands-on quantum algorithm development experience
  • Expertise in quantum programming languages (Q#, Qiskit, Cirq)
  • Strong background in quantum error correction and fault tolerance
  • Proven track record of peer-reviewed publications in quantum computing
  • Experience with quantum hardware platforms (IBM Quantum, Rigetti, IonQ)
  • Ability to secure research funding through grant proposals
  • Excellent communication skills for technical and non-technical audiences

Required Skills

Quantum Computing Qiskit Q# Quantum Algorithms Fault Tolerance Quantum Error Correction Research Methodology Machine Learning High-Performance Computing

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