Job Description
Join the forefront of technological revolution at Nexus Quantum Solutions, where we're pioneering the next era of computational power. We're seeking a visionary Quantum Computing Research Scientist to architect breakthrough solutions that will redefine industries in 2026 and beyond. In this pivotal role, you'll collaborate with Nobel laureates and industry disruptors to harness quantum mechanics for real-world applications.
Our state-of-the-art research center in San Francisco offers unparalleled resources, including access to quantum annealers, superconducting qubit arrays, and a 10,000 sq ft quantum simulation lab. You'll work on projects spanning cryptography optimization, drug discovery acceleration, and climate modeling systems that will impact billions of lives.
We offer a competitive compensation package with equity, flexible work arrangements, and dedicated research funding. Your contributions will directly shape how humanity solves its most complex challenges.
Responsibilities
- Design and implement novel quantum algorithms for NP-hard optimization problems
- Lead cross-functional teams in developing quantum error correction protocols
- Collaborate with hardware engineers to bridge theoretical models with physical qubit implementations
- Publish groundbreaking research in top-tier journals (Nature, Science, etc.)
- Secure $5M+ in government and industry research grants
- Mentor postdoctoral researchers and PhD candidates
- Develop patentable quantum computing methodologies with commercial applications
Qualifications
- PhD in Quantum Physics, Computer Science, or Mathematics with 3+ years industry experience
- Expertise in quantum programming languages (Q#, Qiskit, Cirq)
- Published research in quantum error correction or topological quantum computing
- Proficiency with quantum circuit design and simulation frameworks
- Experience with cloud-based quantum computing platforms (IBM Q, Amazon Braket)
- Demonstrated ability to secure federal research grants (NSF, DARPA, DOE)
- Strong background in machine learning and high-performance computing