About this role
Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Minimum qualifications:
- PhD in Computer Science, Machine Learning, Cognitive Science, Neuroscience, Economics, Sociology, Anthropology, Philosophy or a related technical field.
- 2 years of experience publishing research in core machine learning venues (e.g., NeurIPS, ICML, ICLR, JMLR, TMLR, etc.).
Preferred qualifications:
- Experience constructing and evaluating multi-agent systems, environments, or behavioral research sandboxes.
- Experience with interdisciplinary research on topics that fall outside of those covered by the core machine learning venues (e.g., cognitive science, tech policy and governance, social sciences, etc.).
- Experience writing perspective/review style articles on technical topics.
- Deep understanding and interest in artificial general intelligence and its potential for broader societal impacts.
- Familiarity with institutional analysis frameworks and collective action models.
- Drive research on mapping post-AGI societal dynamics using interdisciplinary computational and theoretical methods.
- Collaborate with social scientists, philosophers, and machine learning researchers to study the impact of AGI on society.
- Design, formalize, simulate, and evaluate multi-agent environments to model societies and large-scale agent collectives.
- Stay current with the latest research literature and advancements across multi-agent AI research, LLMs, game theory, AI safety/ethics/governance, and other relevant social science or philosophy topics.