Job Description
Join Nexus Quantum Labs at the forefront of technological evolution as we pioneer the convergence of quantum computing and artificial intelligence for 2026. We seek a visionary Quantum AI Research Scientist to architect breakthrough systems that will redefine computational paradigms. This role offers unparalleled opportunity to shape the next generation of quantum-AI hybrid technologies in our state-of-the-art San Francisco laboratory.
Our team operates at the intersection of theoretical physics and machine learning, developing algorithms that leverage quantum supremacy to solve previously intractable problems. You will collaborate with Nobel laureates and industry pioneers to prototype quantum neural networks, optimize quantum machine learning pipelines, and publish groundbreaking research in Nature and Science.
Responsibilities
- Design and implement quantum-AI hybrid algorithms for optimization, simulation, and generative modeling
- Lead development of quantum neural network architectures leveraging qubit coherence techniques
- Collaborate with hardware teams to co-design quantum processors optimized for ML workloads
- Author peer-reviewed publications and white papers on quantum machine learning advancements
- Secure $5M+ in DARPA/NASA research grants for quantum-AI initiatives
- Mentor PhD researchers in quantum information theory and computational complexity
- Develop ethical frameworks for quantum AI deployment in regulated industries
Qualifications
- PhD in Quantum Physics, Computer Science, or related field with 3+ years research experience
- Expertise in quantum algorithms (Shor's, Grover's, VQE) and quantum error correction
- Proficiency in quantum programming languages (Q#, Qiskit, Cirq) and ML frameworks (PyTorch, TensorFlow)
- Published research in quantum machine learning or quantum complexity theory
- Deep understanding of NISQ-era hardware limitations and error mitigation strategies
- Experience securing federal research grants and managing multi-institution projects
- Strong background in ethical AI governance and responsible innovation frameworks