Job Description
Join the quantum revolution at NexaTech Innovations, where we're engineering the future of computational science. As a Quantum Computing Research Scientist, you'll pioneer breakthroughs that will redefine industries—from cryptography to AI—by 2026. Our state-of-the-art lab in San Francisco offers an unparalleled environment to collaborate with Nobel laureates and disrupt traditional computing paradigms. We provide competitive equity, flexible work arrangements, and resources to publish groundbreaking research in top-tier journals.
This role demands a blend of theoretical brilliance and hands-on experimentation. You'll lead projects that harness quantum superposition and entanglement to solve problems deemed impossible for classical computers. If you're driven to transform theoretical physics into tangible innovations, NexaTech is your launchpad.
Responsibilities
- Design and implement novel quantum algorithms for optimization, simulation, and machine learning applications.
- Lead research in quantum error correction protocols to achieve fault-tolerant quantum systems.
- Collaborate with hardware teams to prototype and test quantum circuits on superconducting and photonic platforms.
- Develop hybrid quantum-classical frameworks for real-world industrial applications.
- Secure $1M+ in research funding through NSF and DoD grants.
- Mentor PhD candidates and publish 2+ high-impact papers annually.
- Drive open-source initiatives in quantum software development.
Qualifications
- PhD in Quantum Physics, Computer Science, or related field with 5+ years of quantum research experience.
- Expertise in quantum programming languages (Q#, Qiskit, Cirq) and simulation tools.
- Published record in Nature/Science or equivalent-tier journals on quantum information theory.
- Proven ability to translate theoretical models into scalable quantum circuits.
- Deep understanding of quantum decoherence mitigation and topological qubit architectures.
- Experience securing government and corporate research funding.
- Strong background in linear algebra, group theory, and computational complexity.