Job Description
Join Nexus Quantum Labs at the forefront of 2026's technological revolution! We're seeking visionary Quantum AI Research Scientists to pioneer next-generation computational paradigms that will redefine humanity's digital future. Our interdisciplinary team operates at the intersection of quantum mechanics, artificial intelligence, and predictive analytics to solve previously unsolvable challenges in climate modeling, drug discovery, and autonomous systems.
As a key innovator in our San Francisco R&D hub, you'll collaborate with Nobel laureates and industry disruptors to develop proprietary quantum algorithms and hybrid AI-quantum architectures. We offer competitive equity packages, flexible research budgets, and unparalleled access to our 256-qubit quantum processing infrastructure.
Responsibilities
- Design and implement novel quantum machine learning frameworks for predictive analytics
- Lead breakthrough research in quantum neural networks and quantum-classical hybrid systems
- Develop proprietary quantum algorithms for optimization and simulation problems
- Collaborate with cross-functional teams to integrate quantum solutions into commercial applications
- Publish findings in top-tier journals and present at global quantum computing conferences
- Secure patents and intellectual property for quantum AI innovations
- Mentor junior researchers in quantum computing methodologies
Qualifications
- PhD in Quantum Computing, Physics, Computer Science, or related field (or equivalent research experience)
- Expertise in quantum programming languages (Qiskit, Cirq, Q#) and quantum circuit design
- Proven track record of publishing in quantum machine learning or quantum algorithms
- Strong background in advanced mathematics (linear algebra, probability, information theory)
- Experience with high-performance computing architectures and parallel processing
- Proficiency in Python, TensorFlow/PyTorch, and quantum simulation frameworks
- Demonstrated ability to translate complex theoretical concepts into practical implementations