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Research Scientist, Philosophy and Human Values, DeepMind

DeepMind·London·Hybrid·Posted today

Google DeepMind is a London-headquartered AI research lab behind AlphaGo and AlphaFold. They're hiring a Research Scientist in Philosophy and Human Values to study how advanced AI systems can reflect human values, based in London on a hybrid basis. This research role sits within the UK's frontier AI sector.

Minimum qualifications:

  • PhD degree in Philosophy, Political Science, Economics, Law, Psychology, Computer Science, or a related field, or equivalent practical experience.
  • 3 years of research experience in one or more focus areas (such as value alignment, AI institutions and governance, human-AI relationships, or the societal impact of AGI).
  • Experience working with Artificial Intelligence and Machine Learning.

Preferred qualifications:

  • Experience in applying experimental ideas and developing new methodological approaches when needed.
  • Experience effectively communicating research findings to technical and non-technical audiences.
  • Experience identifying core research questions and applying responsible AI principles.
  • Cross-functional collaboration experience, including working across different timezones.
  • A strong track record of publication on AI-related topics.

About the job

At DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. We are seeking a motivated Research Scientist to join our team and contribute to groundbreaking research that will help uncover the path to positive Artificial General Intelligence (AGI) futures. Key questions surround the philosophy of artificial intelligence, including ethics, human values and alignment.

We are seeking a Research Scientist to explore foundational philosophical questions about AGI and its potential impact on the world, including those concerning ethics and alignment. Key responsibilities include defining critical research questions across different domains, collaborating with cross-functional teams to develop innovative solutions, and conducting experiments to advance our mission.

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.

Responsibilities

  • Guide research projects exploring the influence of AGI on domains such as philosophy, political institutions, sociology, economics, law and human relationships.
  • Develop and conduct in-depth studies to understand the philosophical implications of AGI, helping to ensure that it is robustly aligned with human values.
  • Engage in collaborative efforts with cross-functional teams, including external partners, to drive research forward.
  • Conduct deep research into specific areas to improve our understanding of the impact of AGI, and create the map of potential outcomes.
  • Build and refine measurement infrastructure and evaluation frameworks for a systematic evaluation of AGI.
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About DeepMind

Google DeepMind is an AI research laboratory focused on building artificial general intelligence. Founded in London in 2010 by Demis Hassabis, Shane Legg, and Mustafa Suleyman, the company was acquired by Google in 2014 for approximately $660M. DeepMind pioneered breakthroughs including AlphaGo, the first program to defeat a world champion at Go, and AlphaFold, which solved the 50-year-old protein folding problem and has been used by over two million researchers worldwide. The lab remains headquartered in London with a large UK engineering presence and continues to push the boundaries of reinforcement learning, large language models, and scientific AI.

Stage: AcquiredLondon
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