Job Description
Join Nexus Quantum Labs at the forefront of technological evolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking a visionary Quantum Computing Research Scientist to develop next-generation algorithms and architectures that will redefine computational boundaries. In this role, you'll collaborate with Nobel laureates and industry disruptors in our state-of-the-art San Francisco laboratory, leveraging cutting-edge quantum processors to solve humanity's most complex challenges.
Our team operates at the intersection of physics, computer science, and artificial intelligence, pushing the limits of what's possible in quantum supremacy. You'll contribute to breakthroughs in cryptography, material science, and AI optimization while shaping the ethical frameworks that will guide quantum adoption globally.
Responsibilities
- Design and implement novel quantum algorithms for optimization and simulation problems
- Lead experimental validation of quantum circuits on superconducting and photonic platforms
- Develop hybrid quantum-classical machine learning frameworks for 2026-era applications
- Author peer-reviewed publications and patent disclosures for quantum innovations
- Mentor junior researchers in quantum error correction and fault-tolerant architectures
- Collaborate with hardware teams to define next-generation quantum processor specifications
- Represent Nexus Quantum Labs at international quantum technology conferences
Qualifications
- PhD in Physics, Computer Science, or related field with 3+ years quantum research experience
- Publication record in top-tier journals (Nature, Science, PRL) on quantum computing
- Expertise in quantum programming languages (Qiskit, Cirq, Q#) and simulation frameworks
- Deep understanding of quantum error correction and fault-tolerant architectures
- Experience with quantum hardware platforms (superconducting qubits, ion traps, photonics)
- Strong background in linear algebra, group theory, and complexity theory
- Proven ability to translate theoretical concepts into experimental implementations