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Quantum Computing Research Lead

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

Job Description

Join Nexus Quantum Labs at the forefront of technological revolution! We're seeking a visionary Quantum Computing Research Lead to architect the next generation of computational paradigms. Shape the future by pioneering breakthroughs in quantum algorithms, error correction, and scalable hardware. Collaborate with Nobel laureates and industry pioneers in our state-of-the-art Austin facility. This is your opportunity to transform theoretical physics into practical applications that will redefine industries by 2026 and beyond.

Responsibilities

  • Lead quantum algorithm development for optimization, cryptography, and machine learning applications
  • Design and implement error-correction protocols for fault-tolerant quantum systems
  • Collaborate with hardware teams to integrate quantum processors with classical computing frameworks
  • Publish high-impact research in peer-reviewed journals and industry conferences
  • Secure federal grants and corporate partnerships for quantum research initiatives
  • Mentor a cross-disciplinary team of physicists, computer scientists, and engineers
  • Develop roadmaps for quantum advantage in pharmaceuticals, logistics, and AI

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field with 5+ years industry experience
  • Proven track record of publishing quantum computing research in top-tier journals
  • Expertise in quantum programming languages (Q#, Qiskit, Cirq) and simulation frameworks
  • Deep understanding of quantum error correction codes and fault-tolerance architectures
  • Experience securing research funding from DARPA, NSF, or corporate partners
  • Strong background in machine learning and high-performance computing
  • Ability to translate complex quantum concepts into strategic business opportunities

Required Skills

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

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