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Quantum Computing Research Scientist

Nexus Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Join Nexus Labs at the forefront of 2026's quantum revolution. We're seeking a visionary Quantum Computing Research Scientist to develop next-gen algorithms and protocols that will redefine computational boundaries. Our Austin-based team operates at the intersection of theoretical physics and practical applications, working on projects that could transform cryptography, AI, and materials science. You'll collaborate with Nobel laureates and industry pioneers in a state-of-the-art facility equipped with cutting-edge quantum processors. This role offers unparalleled opportunities to shape the technological landscape of the coming decade.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and machine learning applications
  • Lead research initiatives in quantum error correction and fault-tolerant computing architectures
  • Develop hybrid quantum-classical workflows for real-world problem-solving
  • Publish breakthrough research in top-tier journals and present at international conferences
  • Collaborate with engineering teams to translate theoretical models into scalable implementations
  • Mentor junior researchers and contribute to quantum education initiatives

Qualifications

  • PhD in Physics, Computer Science, or related quantum field with 3+ years post-doctoral experience
  • Proven expertise in quantum programming languages (Q#, Qiskit, Cirq)
  • Strong background in quantum information theory and many-body physics
  • Published research in quantum computing or quantum algorithms
  • Experience with high-performance computing and parallel processing frameworks
  • Demonstrated ability to secure competitive research grants and funding
  • Excellent communication skills for cross-functional collaboration

Required Skills

Quantum Computing Qiskit Q# Quantum Algorithms Quantum Error Correction High-Performance Computing Theoretical Physics Machine Learning

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