Job Description
Join Nexus Quantum Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking a visionary Quantum Computing Research Scientist to architect breakthrough algorithms that will redefine computational boundaries. Our interdisciplinary team operates at the intersection of physics, computer science, and AI, developing quantum systems that solve previously unsolvable problems.
About the Role: You'll lead cutting-edge research in quantum error correction, quantum machine learning, and topological qubit systems. Collaborate with Nobel laureates and industry pioneers in our state-of-the-art quantum lab, while contributing to patents that will shape the next decade of technological advancement. This isn't just a job—it's your chance to build the computational foundation for humanity's future.
What We Offer:
- Unlimited quantum computing resources via our proprietary cloud platform
- Equity in a pre-IPO quantum technology leader
- Annual research stipend for conference attendance and equipment
- Flexible remote/hybrid work with quarterly in-person innovation sprints
Responsibilities
- Design and implement novel quantum algorithms for optimization, simulation, and cryptography
- Develop error mitigation protocols for NISQ-era quantum processors
- Lead cross-functional research projects with hardware and AI teams
- Publish findings in top-tier journals (Nature, Science, Quantum) and present at major conferences
- Architect quantum machine learning frameworks for 2026-era applications
- Mentor PhD candidates and postdoctoral researchers
- Secure government and industry grants for quantum research initiatives
Qualifications
- PhD in Quantum Physics, Computer Science, or Electrical Engineering (postdoc preferred)
- 3+ years hands-on experience with quantum programming (Qiskit, Cirq, Q#)
- Published research in quantum algorithms or quantum error correction
- Expertise in linear algebra, group theory, and quantum information theory
- Proficiency with high-performance computing frameworks (HPC, GPU acceleration)
- Strong background in machine learning and classical optimization
- Track record of securing research funding (NSF, DARPA, industry grants)