Job Description
Join Nexus Labs at the forefront of technological revolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking visionary Quantum Computing Research Scientists to develop breakthrough algorithms, optimize quantum hardware performance, and solve previously unsolvable computational challenges. Our team operates at the intersection of theoretical physics, advanced mathematics, and cutting-edge engineering to redefine the boundaries of possibility.
As a key member of our Quantum Innovation Division, you'll collaborate with Nobel laureates, industry pioneers, and government agencies to accelerate quantum adoption across healthcare, logistics, and AI. We offer unparalleled resources, including access to quantum annealers, superconducting qubit systems, and a $50M research budget.
Responsibilities
- Design and implement novel quantum algorithms for optimization, simulation, and machine learning applications
- Develop error correction protocols to enhance qubit stability and quantum gate fidelity
- Collaborate with hardware engineers to co-design next-generation quantum processors
- Lead research initiatives in quantum-resistant cryptography and post-quantum security
- Publish breakthrough research in Nature Physics, Science, and IEEE journals
- Secure $5M+ in government and industry research grants
- Mentor PhD candidates and postdoctoral researchers in quantum information science
Qualifications
- PhD in Quantum Computing, Physics, Computer Science, or related field
- 3+ years of hands-on experience with quantum programming frameworks (Qiskit, Cirq, or Q#)
- Published research in quantum algorithm development or quantum error correction
- Expertise in quantum circuit optimization and quantum machine learning
- Proficiency in high-performance computing and parallel programming
- Strong background in linear algebra, probability theory, and quantum mechanics
- Experience securing government research grants (NSF, DARPA, DOE)
- Track record of translating theoretical concepts into practical implementations