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Quantum Computing Research Lead

Nexus Dynamics
Austin
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Join Nexus Dynamics at the forefront of technological evolution as we pioneer solutions for 2026 and beyond. We seek a visionary Quantum Computing Research Lead to architect next-generation computational paradigms. This role demands a blend of theoretical expertise and practical implementation in quantum algorithms, cryptography, and machine learning. You'll lead a multidisciplinary team pushing the boundaries of quantum supremacy while developing commercially viable applications for finance, healthcare, and logistics.

Our Austin hub offers state-of-the-art quantum annealing facilities and collaborative R&D spaces. We provide competitive equity packages, flexible work arrangements, and dedicated innovation time for cutting-edge exploration.

Responsibilities

  • Design and implement quantum algorithms for complex optimization problems
  • Lead cross-functional teams in quantum cryptography and secure communications
  • Develop hybrid quantum-classical machine learning frameworks
  • Collaborate with industry partners on quantum computing applications
  • Author peer-reviewed research and patent innovations
  • Mentor junior researchers and foster a culture of quantum excellence
  • Secure research funding through NSF, DoE, and corporate partnerships

Qualifications

  • PhD in Quantum Computing, Physics, or Computer Science
  • 5+ years of quantum algorithm development experience
  • Proficiency with quantum programming languages (Q#, Qiskit, Cirq)
  • Published research in top-tier quantum computing journals
  • Expertise in quantum error correction and fault tolerance
  • Strong background in high-performance computing environments
  • Proven track record of translating research into commercial applications
  • Excellent communication skills for technical and non-technical audiences

Required Skills

quantum computing quantum algorithms cryptography machine learning Q# Qiskit Cirq fault tolerance optimization algorithms

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