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Google

Research Scientist, Multi-Agent Systems and Game Theory (Post-AGI Futures), DeepMind

Google · DeepMind

London

Mid-level

AI / ML

Last seen 4h ago

Posted
3d ago

Posted on 6 November 2026

Workplace
Not specified

Work model not stated

Salary
Not disclosed

Salary range not shared by the company

Visa sponsorship
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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.

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.

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.

About Google

Google runs core product engineering out of London, Dublin, Zurich, Warsaw and Munich — not support functions. Zurich is one of its largest engineering sites anywhere, and Warsaw has grown substantially. The bar is high and the process is long, but these are genuine product teams.