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Quantum Computing Research Lead

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

Job Description

Join Nexus Future Labs at the forefront of 2026's quantum revolution. We're pioneering next-gen computational systems that will redefine global industries. As a Quantum Computing Research Lead, you'll architect breakthrough algorithms and lead cross-disciplinary teams solving humanity's most complex challenges. Our Austin campus offers unparalleled resources including 128-qubit processors and AI-assisted research environments. This role combines deep technical expertise with visionary leadership to shape the computational landscape of tomorrow.

Responsibilities

  • Design and implement quantum algorithms for optimization, cryptography, and machine learning applications
  • Lead a team of 5-8 quantum physicists and software engineers in high-impact research initiatives
  • Collaborate with government agencies and Fortune 500 partners on classified and commercial quantum projects
  • Develop patent-pending quantum error correction methodologies for fault-tolerant systems
  • Pioneer hybrid quantum-classical computing frameworks for enterprise-scale deployments
  • Present breakthrough findings at premier conferences and publish in Nature/Science journals

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field with 8+ years of quantum research experience
  • Published work in quantum computing algorithms or quantum information theory
  • Expertise in quantum circuit design using Qiskit, Cirq, or similar frameworks
  • Proven track record of leading high-stakes R&D initiatives with measurable outcomes
  • Deep understanding of quantum decoherence and error correction methodologies
  • Experience securing DoD/NASA grants and managing classified research protocols
  • Strong background in machine learning and high-performance computing architectures

Required Skills

Quantum Computing Quantum Algorithms Qiskit Cryptography Machine Learning High-Performance Computing Quantum Error Correction Research Leadership Scientific Publishing

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