Job Description
Join QuantumLeap Dynamics at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking a visionary Research Scientist to architect the future of computational science in our state-of-the-art San Francisco lab. Collaborate with Nobel laureates and disrupt industries from healthcare to finance by solving problems once deemed impossible. Your work will directly shape the quantum algorithms powering next-gen AI, cryptography, and materials science.
As part of our elite Quantum Innovation Group, you'll access unprecedented resources: 512-qubit quantum processors, dedicated supercomputing clusters, and industry partnerships with NASA and MIT. We offer unparalleled autonomy to explore theoretical breakthroughs while receiving mentorship from quantum pioneers. Our culture celebrates intellectual curiosity with flexible schedules, sabbatical programs, and funding for patent filings.
Responsibilities
- Design and implement novel quantum algorithms for optimization, simulation, and machine learning applications
- Lead cross-functional projects integrating quantum solutions with classical computing systems
- Publish groundbreaking research in Nature/Science journals and present at IEEE Quantum Week
- Develop quantum error correction protocols for fault-tolerant computing architectures
- Collaborate with hardware teams to co-design quantum processors and control systems
- Secure $2M+ in annual research grants from NSF and DoE quantum initiatives
- Mentor PhD interns and contribute to QuantumLeap's open-source quantum frameworks
Qualifications
- PhD in Quantum Physics, Computer Science, or Applied Mathematics with 3+ years quantum research experience
- Publication record in top-tier journals (Nature, Science, PRL) or quantum computing conferences
- Proficiency in quantum programming languages (Q#, Qiskit, Cirq) and simulation frameworks
- Expertise in quantum error correction, topological quantum computing, or variational algorithms
- Strong background in linear algebra, group theory, and statistical mechanics
- Experience with high-performance computing (HPC) and GPU acceleration
- Demonstrated ability to translate theoretical concepts into experimental implementations