Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead groundbreaking research in game theory and AI, pushing the boundaries of strategic intelligence.
- Company: Join Google DeepMind, a leader in AI innovation for public benefit.
- Benefits: Competitive salary, diverse team, and opportunities for impactful research.
- Why this job: Make a real difference in AI safety and ethics while advancing your career.
- Qualifications: PhD in relevant field and strong publication record in machine learning or game theory.
- Other info: Collaborative environment with mentorship opportunities and a commitment to diversity.
The predicted salary is between 28800 - 48000 £ per year.
Overview
Research Scientist, Game Theory & Multi-Agent Systems — Google DeepMind
Join to apply for the Research Scientist, Game Theory & Multi-Agent Systems role at Google DeepMind.
The Game Theory Research Team seeks to achieve foundational breakthroughs in our understanding of strategic intelligence, cooperation, and emergent behaviour in AI systems. We publish our work in premier academic venues to advance the field and to steer the future of AI towards safe and socially beneficial outcomes.
Role
As a Research Scientist, you will work on high-impact research projects that push the boundaries of game theory and AI. You will be responsible for formulating new theories, designing novel algorithms, and driving the intellectual agenda of the team.
Responsibilities
- Conceive and lead a long-term research program in areas such as equilibrium computation, learning dynamics, mechanism design for AI, or emergent communication.
- Publish influential papers in top-tier conferences (e.g., NeurIPS, ICML, AAAI, AAMAS, EC) and contribute to the wider scientific community.
- Design and conduct rigorous experiments to validate theoretical claims, collaborating with Research Engineers to test hypotheses at scale.
- Prototype novel algorithms and models, primarily using JAX to rapidly test and iterate on new ideas.
- Mentor junior researchers and interns, and act as a thought leader on the strategic and safety implications of multi-agent AI, both within Google and externally.
Qualifications
Minimum Qualifications:
- PhD in Computer Science, Economics, Statistics, or a related field.
- A strong record of influential publications in top-tier machine learning or game theory venues.
- Experience prototyping and evaluating ML models in Python.
Preferred Qualifications:
- Internationally recognized research in algorithmic game theory, learning in games, mean-field games, evolutionary game theory, or multi-agent reinforcement learning (MARL).
- Deep mathematical fluency and a track record of proving rigorous theoretical results.
- Hands-on experience prototyping complex research ideas in JAX.
- Experience setting a research agenda and leading long-term, multi-person research collaborations.
Equality and Accessibility: Google DeepMind values diversity of experience, knowledge, backgrounds and perspectives and is committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please let us know.
Application Deadline: 10th October
#J-18808-Ljbffr
Research Scientist, Game Theory & Multi-Agent Systems employer: Google DeepMind
Contact Detail:
Google DeepMind Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist, Game Theory & Multi-Agent Systems
✨Network Like a Pro
Get out there and connect with folks in the AI and game theory space! Attend conferences, join online forums, or hit up local meetups. The more people you know, the better your chances of landing that dream role.
✨Show Off Your Work
Don’t just sit on your research – share it! Publish your findings on platforms like ResearchGate or even your own blog. This not only showcases your expertise but also gets your name out there in the community.
✨Tailor Your Approach
When reaching out to potential employers, make sure to tailor your message. Highlight how your skills in game theory and multi-agent systems align with their projects. Personal touches can make all the difference!
✨Apply Through Our Website
We encourage you to apply directly through our website for the best chance at getting noticed. It’s the quickest way to get your application in front of the right people and show your enthusiasm for joining our team!
We think you need these skills to ace Research Scientist, Game Theory & Multi-Agent Systems
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Research Scientist. Highlight your relevant experience in game theory and multi-agent systems, and don’t forget to showcase those influential publications!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and how your research aligns with our mission at Google DeepMind. Keep it engaging and personal.
Showcase Your Research Impact: When detailing your past projects, focus on the impact of your research. Mention any collaborations, experiments, or algorithms you’ve developed that have made a difference in the field.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and get you into our system quickly!
How to prepare for a job interview at Google DeepMind
✨Know Your Research Inside Out
Before the interview, dive deep into your past research and publications. Be ready to discuss your methodologies, findings, and how they relate to game theory and multi-agent systems. This will show your passion and expertise in the field.
✨Prepare for Technical Questions
Expect to face technical questions that test your understanding of algorithms and game theory concepts. Brush up on key theories and be prepared to solve problems on the spot. Practising with peers can help you articulate your thought process clearly.
✨Showcase Your Collaboration Skills
Since the role involves mentoring and collaborating with others, be ready to share examples of successful teamwork. Highlight any experiences where you led a project or worked closely with engineers to achieve a common goal.
✨Discuss Future Research Directions
Think about where you want to take your research in the future. Be prepared to discuss potential long-term projects and how they align with the team's goals. This shows initiative and a forward-thinking mindset, which is crucial for a pioneering role.
