Job Description
Join Nexus Quantum Labs at the forefront of computational revolution as we pioneer breakthroughs that will redefine 2026's technological landscape. We're seeking a visionary Quantum Computing Research Scientist to develop scalable quantum algorithms and hardware solutions that will transform industries from pharmaceuticals to cryptography. In this role, you'll collaborate with Nobel laureates and industry pioneers in our state-of-the-art Austin facility, pushing the boundaries of quantum supremacy.
Our team operates at the intersection of theoretical physics and practical application, with access to IBM Quantum and Rigetti systems. You'll contribute to projects with direct commercial impact, including quantum machine learning frameworks and error-correction protocols. We offer unparalleled resources including our proprietary quantum annealing processors and $50M annual R&D budget.
Responsibilities
- Design and implement novel quantum algorithms for optimization and simulation problems
- Develop quantum error correction protocols for fault-tolerant computing systems
- Lead cross-functional teams in prototyping quantum hardware interfaces
- Publish research in top-tier journals (Nature, Science, Quantum) and industry conferences
- Collaborate with product teams to commercialize quantum solutions for 2026 market readiness
- Secure federal and private research grants (NSF, DARPA, industry partnerships)
- Mentor PhD candidates and junior researchers in quantum methodologies
Qualifications
- PhD in Quantum Physics, Computer Science, or related field (postdoc preferred)
- 5+ years of hands-on quantum computing experience with gate-based systems
- Published research in quantum algorithm development or hardware optimization
- Proficiency in Qiskit, Cirq, or equivalent quantum programming frameworks
- Deep understanding of quantum decoherence and error correction techniques
- Track record of securing $500K+ in research funding
- Experience with cryogenic quantum systems and superconducting qubits
- Strong background in linear algebra and computational complexity theory