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Quantum Computing Research Scientist

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Join Nexus Future Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. Our multidisciplinary team of visionaries is developing next-gen quantum algorithms that will redefine industries, from pharmaceuticals to cryptography. This is your chance to shape the future of computation in an environment where curiosity meets cutting-edge resources. We offer unparalleled research autonomy, state-of-the-art lab facilities, and collaboration with Nobel laureates. If you're passionate about solving humanity's most complex problems through quantum mechanics, this is the role you've been waiting for.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and simulation challenges
  • Lead breakthrough research in quantum error correction and fault-tolerant systems
  • Collaborate with hardware teams to translate theoretical models into practical quantum processors
  • Publish findings in top-tier journals and present at international conferences
  • Mentor junior researchers and drive cross-functional innovation
  • Secure external funding through NSF and DARPA grants
  • Develop patentable quantum computing methodologies

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field
  • 3+ years of hands-on quantum algorithm development experience
  • Proficiency in quantum programming frameworks (Qiskit, Cirq, or Q#)
  • Strong publication record in quantum computing or theoretical physics
  • Deep understanding of quantum entanglement and superposition principles
  • Experience with high-performance computing architectures
  • Demonstrated ability to translate complex theories into practical applications

Required Skills

Quantum Computing Quantum Algorithms Qiskit Cirq Quantum Error Correction Theoretical Physics High-Performance Computing Machine Learning

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