Job Description
Join Nexus Future Labs at the forefront of technological evolution as we pioneer the next frontier of human-machine collaboration. We seek a visionary Quantum AI Research Scientist to architect breakthrough systems that will redefine industries by 2026. In this pivotal role, you'll develop hybrid quantum-neural architectures that solve previously impossible computational challenges while ensuring ethical AI deployment. Our multidisciplinary teams collaborate in state-of-the-art labs where theoretical physics meets practical innovation, pushing boundaries in cryptography, drug discovery, and autonomous systems.
You'll lead experimental trials at our quantum computing facilities, publish findings in top-tier journals, and translate research into commercial applications with our industry partners. This position offers unparalleled resources including access to 1000-qubit quantum processors and dedicated AI supercomputing clusters. If you're driven to solve humanity's grandest challenges through quantum-AI convergence, this is your moment to shape the future.
Responsibilities
- Design and implement hybrid quantum-AI algorithms for complex optimization problems in logistics, finance, and healthcare
- Lead experimental validation of quantum neural networks on real-world datasets with 99.9% accuracy targets
- Develop ethical AI governance frameworks for quantum decision systems with built-in bias mitigation
- Collaborate with hardware engineers to co-design quantum processors optimized for machine learning workloads
- Publish 2-3 high-impact research papers annually in Nature/Science journals
- Mentor junior researchers through our Quantum-AI Fellowship program
- Translate theoretical breakthroughs into scalable commercial applications with Fortune 500 partners
- Present findings at international conferences including IEEE Quantum Week and AI Frontiers
Qualifications
- PhD in Quantum Computing, Machine Learning, or Computational Physics with 5+ years research experience
- Published work in top-tier quantum/AI journals with demonstrated impact on industry applications
- Expertise in quantum circuit design using Qiskit/PyTorch Quantum frameworks
- Proficiency in Python/C++ with optimization libraries (Cirq, PennyLane)
- Strong background in quantum error correction and fault-tolerant architectures
- Experience with large-scale distributed computing systems (Spark, Kubernetes)
- Track record of securing government/industry grants for quantum research
- Deep understanding of quantum advantage benchmarks and NISQ-era limitations