Job Description
Join Nexus Labs at the forefront of 2026's technological revolution as we pioneer quantum-AI integration for next-generation computational systems. We're seeking visionary researchers to develop hybrid quantum-neural algorithms that will redefine machine learning paradigms. Our state-of-the-art facility in San Francisco offers unparalleled resources for groundbreaking research in quantum supremacy, error correction, and scalable quantum computing architectures. Collaborate with Nobel laureates and industry pioneers in an environment where theoretical physics meets practical AI innovation. Enjoy competitive benefits, flexible work arrangements, and dedicated R&D funding for your experimental projects.
Responsibilities
- Design and implement quantum machine learning algorithms for real-world problem-solving
- Lead cross-functional teams in developing quantum-optimized neural networks
- Publish high-impact research in peer-reviewed quantum computing journals
- Develop error mitigation protocols for quantum-AI hybrid systems
- Collaborate with hardware engineers to co-design quantum processors
- Secure federal and private research grants for quantum-AI initiatives
- Mentor junior researchers in quantum computing principles
Qualifications
- PhD in Quantum Computing, Theoretical Physics, or Computer Science
- 3+ years experience with quantum programming frameworks (Qiskit, Cirq, or Q#)
- Published research in quantum machine learning or quantum algorithms
- Proficiency in Python, TensorFlow/PyTorch, and quantum circuit design
- Deep understanding of quantum decoherence and error correction
- Experience with cloud-based quantum computing platforms (IBM Quantum, Amazon Braket)
- Strong background in linear algebra, probability theory, and information theory