Job Description
Join Nexus Innovations at the forefront of technological evolution as we pioneer breakthroughs in quantum artificial intelligence. We're seeking visionary Quantum AI Research Scientists to architect solutions that will redefine computing paradigms by 2026. In this pivotal role, you'll collaborate with Nobel laureates and industry pioneers to develop quantum neural networks, optimize quantum machine learning algorithms, and solve previously unsolvable computational challenges.
Our Austin-based innovation hub offers unparalleled resources including 128-qubit quantum processors, exascale computing clusters, and dedicated quantum-safe infrastructure. You'll lead cross-disciplinary teams of physicists, computer scientists, and ethicists to transform theoretical quantum advantage into practical applications across healthcare, climate modeling, and autonomous systems.
This position includes equity grants, unlimited research budget, and dedicated patent support. Your work will directly influence the trajectory of global technology development while contributing to humanity's most ambitious scientific endeavors.
Responsibilities
- Design and implement novel quantum machine learning architectures leveraging 100+ qubit systems
- Develop hybrid quantum-classical algorithms for optimization problems with exponential speedups
- Lead quantum neural network research achieving 10^6 parameter scaling
- Pioneer quantum-resistant cryptography protocols for post-2026 security frameworks
- Collaborate with MIT and Caltech on quantum-AI co-development initiatives
- Publish 3+ top-tier papers/year in Nature/Science journals
- Secure $2M+ in quantum computing grants annually
- Mentor PhD researchers in quantum machine learning techniques
Qualifications
- PhD in Quantum Computing, Theoretical Physics, or Machine Learning with 5+ years research experience
- Published work in quantum algorithms or quantum machine learning in QIP/ICML venues
- Expertise in Qiskit, Cirq, and quantum circuit optimization frameworks
- Proficiency in tensor networks and quantum simulation methods
- Demonstrated experience with 50+ qubit quantum processors
- Strong background in high-performance computing (HPC) architectures
- Deep understanding of quantum error correction and fault tolerance
- Track record of securing competitive research grants (NSF/DOE/DARPA)