Cambridge Research Intern – Generative Models for Video Games

The Game Intelligence team is seeking highly motivated researcher intern candidates in the area of Gaming and AI, for an internship based in Microsoft Research Cambridge, UK. We encourage applications from all candidates with a background in Deep Learning (DL), Reinforcement Learning (RL), Generative AI (Gen AI), or a related field, who are excited to tackle challenges that arise in applications of modern machine learning approaches to video games. Working closely with the team and other collaborators in Microsoft for the duration of 16 weeks, you will advance the state of the art in this space by building on, comparing to, and leveraging existing models and datasets we have developed and have access to.

This is an exceptional opportunity to work closely with a highly collaborative and interdisciplinary team. Some research challenges that we are currently tackling include, but are not limited to:

• Natural language control of embodied agents
• Test-time compute for multimodal agents
• Training and evaluation of multimodal generative AI models
• Generalization to new games/scenarios
• Model architectures/approaches for faster/improved world modelling
• Alternative approaches for video generation/understanding/compression
• Fine-tuning/adapting pre-trained models with minimal data/compute
• Deeper understanding/mechanistic interpretability of gaming-related foundation models
• Scaling to large-scale data and compute The focus and scope of each internship considers the team’s direction as well as successful candidates’ experience and research interests.

This posting will be active for 30 days, and all candidates applying within this time are considered on an equal basis. When submitting your application, include your CV with a list of

publications as an attachment.

You will be invited to submit contact details for a professional reference – these are optional but recommended. For more information about the post, please feel free to email Tabish Rashid at: tabishrashid@microsoft.com.

Required/Minimum Qualifications:

• Currently enrolled in a Bachelors (BSc) or Masters (required) or PhD (preferred) program in Artificial Intelligence, Machine Learning, Computer Science, Game Development or a related area.

• Ability to carry out research in at least one of the areas mentioned above, demonstrated by at least one journal or conference publication (or demonstratable equivalent experience).

• Strong understanding of state-of-the-art deep learning approaches.

• Hands-on experience in implementing and empirically evaluating deep learning approaches.

• Effective communication skills and ability to work in a collaborative environment.

Preferred/Additional Qualifications:

• Currently enrolled in a PhD program in Artificial Intelligence, Machine Learning, Computer Science, Game Development or a related area.

• Ability to carry out research in at least one of the areas mentioned above, demonstrated by at least one journal or conference publication in one of the top publication venues in your research area.

• Demonstrated ability and/or strong motivation to learn to use cloud infrastructure for experimentation is a plus.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

• In collaboration with your mentor and a diverse team (for example, including designers, engineers, and researchers), contribute to solving an ambitious research challenge and translate your results into actionable insights that are relevant to potential applications in modern video games.
•  Write code and contribute to shared codebases to test the new approach or hypotheses. 
• Distil the developed insights into effective communications, such as a research paper, prototypes, demos and/or a presentation, to reach internal and external technical and general audiences.