Job Description
Join Nexus Future Labs at the forefront of 2026's technological revolution. We're seeking a visionary Quantum AI Research Scientist to pioneer breakthroughs at the intersection of quantum computing and artificial intelligence. As a key member of our elite R&D division, you'll shape the future of computational intelligence while working in our state-of-the-art Austin facility. This role offers unparalleled resources to explore uncharted territories in quantum machine learning algorithms, with direct impact on global industries from healthcare to climate modeling.
Our dynamic culture combines academic rigor with startup agility, offering competitive compensation, flexible work arrangements, and opportunities to present findings at premier international conferences. You'll collaborate with Nobel laureates and industry disruptors while pushing the boundaries of what's computationally possible.
Responsibilities
- Design and implement novel quantum machine learning architectures for 2026-era applications
- Lead cross-functional teams to integrate quantum algorithms into next-gen AI systems
- Publish groundbreaking research in top-tier journals and conferences (Nature, Science, NeurIPS)
- Develop proprietary quantum computing frameworks for complex optimization problems
- Mentor junior researchers and interns in quantum AI methodologies
- Secure external funding through NSF and DARPA proposals
- Collaborate with industry partners to commercialize quantum AI innovations
Qualifications
- PhD in Quantum Computing, AI, or Computational Physics (or equivalent research experience)
- Expertise in quantum algorithms, quantum error correction, and NISQ-era hardware
- Proven track record of peer-reviewed publications in quantum/AI journals
- Proficiency in quantum programming languages (Qiskit, Cirq) and classical ML frameworks
- Experience with high-performance computing clusters and quantum simulators
- Demonstrated ability to translate theoretical concepts into practical implementations
- Strong background in linear algebra, probability theory, and information theory