Job Description
Join Nexus Quantum Labs at the forefront of technological revolution as we pioneer the next frontier of computational power. As a Quantum Computing Research Scientist, you will architect breakthrough solutions for complex global challenges in cryptography, drug discovery, and artificial intelligence. Our state-of-the-art facility in San Francisco offers unparalleled resources to transform theoretical quantum mechanics into practical applications that will define 2026 and beyond.
We seek visionary thinkers who thrive at the intersection of physics, computer science, and innovation. Your work will directly influence how humanity solves previously unsolvable problems while shaping the ethical frameworks for quantum-powered systems. If you're ready to push the boundaries of possibility, this is your moment to leave an indelible mark on the future.
Responsibilities
- Design and implement novel quantum algorithms to solve real-world optimization problems
- Lead experimental quantum computing projects using superconducting qubit systems
- Collaborate with cross-functional teams to develop quantum-resistant encryption protocols
- Publish groundbreaking research in leading scientific journals and industry conferences
- Mentor junior researchers and contribute to quantum computing education initiatives
- Secure external funding through NSF, DARPA, and private sector grants
- Develop error mitigation strategies for practical quantum applications
Qualifications
- PhD in Physics, Computer Science, or related field with quantum computing specialization
- 3+ years of hands-on experience with quantum programming frameworks (Qiskit, Cirq)
- Expertise in quantum error correction and fault-tolerant architectures
- Strong publication record in quantum information science
- Proficiency in Python, C++, and quantum simulation tools
- Demonstrated ability to translate complex quantum concepts into actionable solutions
- Experience securing competitive research grants or industry partnerships
- Knowledge of quantum machine learning algorithms and applications