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Research & Development 🏢 Full Time ⭐️ Verified

Quantum Computing Research Scientist

Nexus Quantum Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
14 Mei 2026
Deadline
14 Mei 2027

Job Description

Join Nexus Quantum Labs at the forefront of computational revolution as we pioneer quantum solutions for 2026's most complex challenges. We're seeking a visionary Quantum Computing Research Scientist to develop next-generation algorithms and hardware prototypes that will redefine industries. You'll collaborate with Nobel laureates in our state-of-the-art Austin facility, working on quantum supremacy projects with direct impact on pharmaceutical discovery, climate modeling, and financial optimization.

This role offers unparalleled resources, including access to our 512-qubit quantum processors and partnership with MIT's Quantum Engineering Center. Your work will shape the quantum landscape for decades to come.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and simulation problems
  • Develop error-correction protocols for fault-tolerant quantum computing systems
  • Lead cross-functional R&D teams in quantum hardware-software co-design
  • Publish breakthrough research in Nature/Science journals and present at IEEE Quantum Week
  • Collaborate with government agencies on quantum security frameworks
  • Mentor PhD candidates in quantum information science

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field with 3+ years postdoc experience
  • Published research in quantum algorithms or quantum error correction
  • Proficiency in quantum programming languages (Qiskit, Cirq, or Q#)
  • Experience with superconducting or trapped-ion quantum processors
  • Strong background in linear algebra, probability theory, and computational complexity
  • Proven track record of securing NSF or DOE quantum research grants

Required Skills

Quantum Computing Quantum Algorithms Error Correction Qiskit Cirq Superconducting Qubits Quantum Simulation Machine Learning Cryptography

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