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Quantum Computing Research Scientist

NexGen Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
22 Mei 2026
Deadline
22 Mei 2027

Job Description

Join NexGen Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking visionary Quantum Computing Research Scientists to develop breakthrough algorithms and hardware prototypes that will redefine computational boundaries. This role offers unparalleled opportunities to collaborate with Nobel laureates and publish in top-tier journals while contributing to projects with global impact.

Our state-of-the-art facility in San Francisco provides an interdisciplinary environment where you'll work alongside experts in quantum physics, materials science, and AI. We offer competitive compensation, flexible work arrangements, and comprehensive benefits including equity packages and wellness stipends.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and simulation problems
  • Develop quantum error correction protocols for fault-tolerant systems
  • Collaborate on quantum hardware prototyping with cryogenic engineering teams
  • Lead research publications in peer-reviewed journals and conferences
  • Translate theoretical concepts into practical quantum computing applications
  • Mentor junior researchers and contribute to patent development

Qualifications

  • PhD in Quantum Computing, Physics, Computer Science, or related field
  • 3+ years of hands-on experience with quantum programming languages (Q#, Qiskit)
  • Publication record in top-tier quantum computing journals
  • Expertise in quantum error correction and fault-tolerant architectures
  • Strong background in linear algebra, probability theory, and complex analysis
  • Experience with superconducting or photonic quantum systems
  • Proven ability to secure research funding through grants and proposals

Required Skills

Quantum Computing Q# Qiskit Quantum Algorithms Cryogenics Superconducting Circuits Machine Learning Research Methodology

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