Job Description
Join InnovateX Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking a visionary Quantum Computing Research Scientist to develop breakthrough algorithms and systems that will redefine computational boundaries. This role offers unparalleled opportunities to work with cutting-edge hardware, collaborate with Nobel laureates, and shape the future of AI, cryptography, and materials science.
Our state-of-the-art facility in San Francisco's innovation hub provides an environment where curiosity meets resources. You'll lead projects with global impact while enjoying competitive benefits, flexible work arrangements, and continuous learning opportunities through our partnership with MIT Quantum Center.
Responsibilities
- Design and implement novel quantum algorithms for optimization, machine learning, and cryptography applications
- Collaborate with hardware teams to develop error-corrected quantum systems with 100+ qubit stability
- Lead research initiatives in quantum machine learning and hybrid quantum-classical computing
- Publish findings in top-tier journals (Nature, Science, Quantum) and present at international conferences
- Secure external funding through NSF, DARPA, and industry partnerships
- Mentor PhD candidates and postdoctoral researchers in quantum computing methodologies
- Translate theoretical breakthroughs into scalable commercial solutions
Qualifications
- PhD in Quantum Physics, Computer Science, or related field with 3+ years of research experience
- Expertise in quantum circuit design, error correction, and quantum algorithm development
- Proficiency with quantum programming frameworks (Qiskit, Cirq, Q#) and high-performance computing environments
- Publication record in quantum computing or theoretical computer science
- Experience with quantum hardware (IBM, Google, Rigetti) or quantum simulation platforms
- Demonstrated ability to secure research grants and manage multi-disciplinary teams
- Strong background in linear algebra, probability theory, and computational complexity