Job Description
Join the forefront of technological revolution as Quantum Computing Research Scientist at Nexus Quantum Labs. As we approach 2026, quantum computing is poised to redefine industries, and we're building the team that will lead this transformation. You'll work in our state-of-the-art Austin facility, collaborating with Nobel laureates and industry pioneers to solve humanity's most complex challenges. We offer competitive compensation, equity packages, and unparalleled resources to accelerate your breakthroughs.
Our multidisciplinary environment combines quantum physics, machine learning, and cybersecurity expertise. You'll have access to cutting-edge quantum processors and 24/7 research labs while contributing to projects that could revolutionize drug discovery, climate modeling, and artificial intelligence. This is more than a job – it's your chance to shape 2026's technological landscape.
Responsibilities
- Design and implement novel quantum algorithms for optimization and simulation problems
- Lead research on quantum error correction and fault-tolerant computing architectures
- Collaborate with hardware teams to bridge theoretical models with practical quantum systems
- Develop quantum machine learning frameworks for next-gen AI applications
- Publish peer-reviewed research and present findings at major quantum conferences
- Mentor junior researchers and drive cross-functional innovation initiatives
- Secure external funding through NSF grants and industry partnerships
Qualifications
- PhD in Quantum Physics, Computer Science, or related field (or equivalent experience)
- 3+ years hands-on experience with quantum programming frameworks (Qiskit, Cirq, Q#)
- Strong publication record in quantum computing or theoretical physics
- Expertise in quantum algorithms and complexity theory
- Proficiency in Python, C++, and quantum circuit design
- Deep understanding of quantum decoherence and noise mitigation
- Experience with high-performance computing environments
- Track record of translating theoretical concepts into practical implementations