Job Description
Shape the future at Nexus Quantum Labs, where quantum computing meets artificial intelligence. We're pioneering the next frontier of computational intelligence and seeking a visionary Quantum AI Research Scientist to lead breakthrough initiatives in 2026 and beyond. Join our elite team at the intersection of quantum mechanics, machine learning, and computational physics.
As a key innovator in our Quantum AI division, you'll design and implement hybrid quantum-classical algorithms that solve previously intractable problems. You'll collaborate with Nobel Prize-winning physicists, AI pioneers, and engineers to develop fault-tolerant quantum systems capable of accelerating drug discovery, optimizing climate models, and revolutionizing cryptography. This role offers unparalleled access to our $500M quantum computing infrastructure and the opportunity to publish groundbreaking research in Nature and Science.
We offer a competitive compensation package including equity, unlimited PTO, comprehensive health benefits, and relocation assistance. Our campus features on-site childcare, gourmet dining, and state-of-the-art wellness facilities. Join us as we build the quantum-powered future.
Responsibilities
- Design and implement novel quantum machine learning algorithms for optimization and pattern recognition
- Develop hybrid quantum-classical neural architectures for exponential computational acceleration
- Lead research in quantum error correction and fault-tolerant computing systems
- Collaborate with cross-functional teams to translate quantum AI prototypes into production solutions
- Author peer-reviewed publications and patents in quantum computing and AI domains
- Mentor junior researchers and contribute to quantum AI curriculum development
- Stay at the forefront of quantum hardware advancements (superconducting, photonic, trapped ion)
Qualifications
- PhD in Quantum Computing, AI, Physics, or Computer Science with 3+ years research experience
- Expertise in quantum algorithms (Shor's, Grover's, VQE, QAOA) and quantum circuit design
- Proficiency in quantum programming frameworks (Qiskit, Cirq, PennyLane) and classical ML libraries
- Published research in top-tier journals/conferences (Nature, Science, NeurIPS, QIP)
- Strong background in linear algebra, probability theory, and computational complexity
- Experience with quantum hardware platforms (IBM Quantum, Rigetti, IonQ, or D-Wave)
- Demonstrated ability to lead complex research projects with cross-disciplinary teams