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Quantum Computing Researcher 2026

Nexus Quantum Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Join Nexus Quantum Labs at the forefront of computational revolution. We're pioneering breakthroughs in quantum algorithms and error correction that will redefine 2026's technological landscape. Our Austin-based R&D hub combines cutting-edge hardware with world-class theoretical physics to solve problems once deemed impossible.

This role offers unparalleled opportunity to shape the next generation of quantum-resistant cryptography and accelerate drug discovery simulations. You'll collaborate with Nobel laureates and MIT alumni in an environment where 15-hour workweeks are replaced by 15-minute breakthroughs.

Responsibilities

  • Design and implement quantum error correction protocols for fault-tolerant systems
  • Develop novel quantum algorithms for optimization and machine learning applications
  • Lead cross-functional teams in prototyping quantum processors at 4K+ qubit scale
  • Publish peer-reviewed research in Nature/Science journals with 90% acceptance rate
  • Secure $2M+ in DARPA/NASA grants for quantum supremacy projects
  • Mentor PhD candidates in quantum information theory
  • Collaborate with IBM/Google quantum hardware teams on standardization

Qualifications

  • PhD in Quantum Physics, Computer Science, or equivalent with 3+ years industry experience
  • Published work in top-tier quantum computing conferences (QIP, TQC)
  • Expertise in Qiskit/Cirq frameworks with 100+ quantum circuits deployed
  • Proficiency in tensor networks and quantum simulation techniques
  • Experience with cryogenic quantum hardware integration
  • Strong background in topological quantum field theories
  • Security clearance eligibility for government-funded projects
  • Portfolio demonstrating quantum algorithm implementations

Required Skills

Quantum Computing Qiskit Cryogenics Topological Quantum Field Theory Quantum Error Correction Tensor Networks Machine Learning DARPA Grants QIP Conference Fault-Tolerant Systems

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