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Quantum Computing Research Scientist

Nexus Quantum Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
24 Mei 2026
Deadline
24 Mei 2027

Job Description

Join Nexus Quantum Labs at the forefront of technological evolution as we pioneer the next generation of computational paradigms. We're seeking visionary Quantum Computing Research Scientists to transform theoretical breakthroughs into revolutionary applications that will redefine industries by 2026. Our state-of-the-art facility in San Francisco offers unparalleled resources to explore quantum supremacy, cryptography, and machine learning. This role represents a unique opportunity to shape humanity's technological future while working alongside Nobel-caliber minds in a culture that celebrates intellectual curiosity and bold innovation.

Responsibilities

  • Lead research initiatives in quantum algorithm development and optimization for practical applications
  • Design and execute complex quantum circuit simulations using cutting-edge frameworks
  • Collaborate with cross-functional teams to integrate quantum solutions into existing systems
  • Publish breakthrough findings in premier scientific journals and industry conferences
  • Mentor junior researchers and contribute to quantum computing educational initiatives
  • Secure research funding through grant proposals and industry partnerships

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field with 3+ years research experience
  • Proficiency in quantum programming languages (Qiskit, Cirq, Q#) and simulation tools
  • Published record in quantum computing or theoretical computer science
  • Deep understanding of quantum error correction and fault-tolerant architectures
  • Experience with machine learning frameworks and their quantum adaptations
  • Strong analytical skills with ability to translate complex theories into testable hypotheses

Required Skills

Quantum Computing Quantum Algorithms Qiskit Cirq Machine Learning Cryptography Theoretical Physics Research Methodology

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