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Research & Development 🏢 Full Time ⭐️ Verified

Quantum Computing Research Scientist

Nexus Labs
San Francisco
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 technological revolution as we pioneer quantum computing solutions for 2026 and beyond. We seek visionary Quantum Computing Research Scientists to develop groundbreaking algorithms and hardware systems that will redefine computational boundaries. Collaborate with world-class physicists, engineers, and AI specialists in our state-of-the-art Silicon Valley facility to solve humanity's most complex challenges.

Why Nexus Labs? We offer unparalleled resources for quantum research, including access to 100+ qubit processors and a $50M annual R&D budget. Our team has published 12 Nature papers in the last 18 months and holds 47 quantum computing patents.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and simulation problems
  • Develop error correction protocols to achieve fault-tolerant quantum computation
  • Lead experimental validation of quantum hardware systems at cryogenic temperatures
  • Collaborate with AI teams to hybridize quantum-classical machine learning frameworks
  • Publish research in top-tier journals (Nature, Science, PRL) and present at major conferences
  • Secure $5M+ in government grants and industry partnerships

Qualifications

  • PhD in Physics, Computer Science, or Electrical Engineering with quantum focus
  • 3+ years of hands-on quantum computing research experience
  • Proficiency in quantum programming languages (Q#, Qiskit, Cirq)
  • Deep understanding of quantum error correction and fault tolerance
  • Publication record in quantum information science
  • Experience with superconducting or ion-trap quantum hardware
  • Strong background in linear algebra and complex analysis

Required Skills

Quantum Computing Qiskit Q# Quantum Error Correction Superconducting Qubits Quantum Algorithms Cryogenics Machine Learning Fault Tolerance

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