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Quantum Computing Research Scientist

Nexus Innovations Inc.
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
24 Mei 2026
Deadline
24 Mei 2027

Job Description

Join Nexus Innovations Inc. at the forefront of technological evolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking visionary Quantum Computing Research Scientists to develop groundbreaking algorithms and hardware prototypes that will redefine computational boundaries. Our interdisciplinary team collaborates in state-of-the-art labs to solve humanity's most complex challenges. Enjoy competitive compensation, flexible work arrangements, and unparalleled opportunities to shape the future of technology.

Responsibilities

  • Design and implement novel quantum algorithms for optimization, cryptography, and machine learning applications
  • Develop quantum hardware prototypes and error-correction methodologies at cryogenic temperatures
  • Collaborate with cross-functional teams to integrate quantum solutions with classical computing systems
  • Lead research initiatives in quantum supremacy and fault-tolerant quantum computing
  • Publish findings in peer-reviewed journals and present at international conferences
  • Secure federal grants and industry partnerships for quantum research projects

Qualifications

  • PhD in Quantum Physics, Computer Science, Electrical Engineering, or related field
  • 5+ years of experience in quantum algorithm development or quantum hardware research
  • Proficiency in quantum programming languages (Q#, Qiskit, Cirq) and simulation tools
  • Strong background in quantum error correction and fault-tolerant architectures
  • Publication record in top-tier quantum computing journals (e.g., Nature Quantum Information)
  • Experience with cryogenic systems and quantum control electronics
  • Excellent written communication skills for technical documentation and grant proposals

Required Skills

Quantum Computing Quantum Algorithms Cryogenic Engineering Quantum Error Correction Qiskit Q# Fault-Tolerant Systems Machine Learning Cryptography

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