Job Description
Join Nexus Labs at the forefront of 2026's technological revolution! We're seeking visionary Quantum AI Research Scientists to pioneer breakthroughs that will redefine humanity's future. In this high-impact role, you'll develop next-generation AI systems leveraging quantum computing principles to solve previously unsolvable challenges in healthcare, climate modeling, and computational biology. Our state-of-the-art facilities in downtown San Francisco offer unparalleled resources, including access to quantum annealers and neural network accelerators. Collaborate with Nobel laureates and Turing Award winners in an environment that celebrates intellectual curiosity and bold innovation. This is your chance to leave an indelible mark on human progress.
Responsibilities
- Design and implement quantum-enhanced machine learning algorithms for complex optimization problems
- Lead cross-functional teams in developing novel AI architectures with quantum-inspired neural networks
- Publish groundbreaking research in top-tier journals and present findings at global conferences
- Partner with industry leaders to commercialize quantum AI solutions in emerging markets
- Mentor junior researchers and establish ethical frameworks for responsible AI development
- Secure government and private funding for cutting-edge research initiatives
- Develop patentable quantum AI methodologies with commercial applications
Qualifications
- PhD in Quantum Computing, Machine Learning, or Computational Physics
- 5+ years of experience in quantum algorithm development or advanced AI research
- Proficiency in quantum programming languages (Qiskit, Cirq) and classical ML frameworks
- Publication record in Nature, Science, or IEEE journals on quantum/AI topics
- Deep understanding of quantum error correction and fault-tolerant computing principles
- Experience securing $1M+ in research grants or venture funding
- Expertise in ethical AI governance and responsible innovation frameworks
- Strong background in computational neuroscience or complex systems modeling