Job Description
Join Nexus Future Labs at the forefront of technological revolution as we pioneer the next generation of quantum computing solutions. We seek a visionary Quantum Computing Research Scientist to develop breakthrough algorithms and systems that will redefine computational capabilities by 2026. This role offers unparalleled opportunities to shape the future of technology while working alongside Nobel laureates and industry pioneers in our state-of-the-art San Francisco facility.
As a key member of our Quantum Innovation Division, you'll tackle complex challenges in quantum error correction, qubit stabilization, and algorithm optimization. Our culture values audacious thinking and collaborative experimentation, with dedicated resources including our 128-qubit quantum processor and cryogenic research labs. We offer competitive equity packages, unlimited PTO, and comprehensive benefits designed for forward-thinking professionals.
Responsibilities
- Design and implement novel quantum algorithms for optimization and simulation problems
- Lead research initiatives in quantum error correction and fault-tolerant systems
- Collaborate with hardware teams to develop quantum processor architectures
- Publish findings in top-tier journals and present at international conferences
- Secure research funding through government grants and industry partnerships
- Mentor junior researchers and foster cross-functional innovation
- Develop roadmaps for quantum computing applications in finance, cryptography, and AI
Qualifications
- PhD in Quantum Physics, Computer Science, or related field with 5+ years research experience
- Expertise in quantum algorithms (Shor's, Grover's, VQE) and quantum circuit design
- Proficiency in quantum programming languages (Q#, Qiskit, Cirq)
- Published research in peer-reviewed journals with significant citations
- Experience with quantum hardware platforms (IBM Quantum, Rigetti, IonQ)
- Demonstrated ability to secure competitive research grants
- Strong background in linear algebra, probability theory, and computational complexity