Google DeepMind Student Researcher Program

The Google DeepMind Student Researcher Program embeds students, primarily PhD candidates with exceptional master’s and undergraduate cases, inside the teams behind AlphaFold and Gemini for paid research placements of roughly three to six months, mostly in London. Participants run experiments at frontier compute scale, with mentorship from leading researchers and realistic paths to co-authored publications.

Openings typically post in early autumn for the following year and close as teams fill, so prepared candidates watch the careers page from September. Applications citing specific DeepMind teams and papers materially outperform generic ones.

• Students in machine learning, computer science, mathematics, neuroscience, physics and related quantitative fields.
• PhD students are the core intake for research roles, with exceptional master's and undergraduate candidates considered in some cycles and engineering tracks.
• Demonstrated research ability: publications, strong theses or substantial open-source and project work.
• Deep grounding in ML fundamentals plus fluency in Python and frameworks like JAX or PyTorch.
• Work authorization per hosting site, with London roles supporting visa sponsorship for many candidates.
• Alignment with active research areas, from LLMs and agents to science applications like AlphaFold's successors.

• Conduct research embedded in a DeepMind team, contributing to projects that can reach publications or product impact.
• Work with world-class researchers behind systems like AlphaGo, AlphaFold and Gemini.
• Design and run experiments at a compute scale universities cannot match.
• Present findings internally and, where possible, co-author papers.
• Join reading groups and talks across one of the world's densest AI research communities.
• Build relationships that shape PhD directions and future roles.

• Competitive paid research placement with relocation support where applicable.
• Access to frontier-scale compute and internal tooling.
• Mentorship from leading researchers in your area.
• Potential publication co-authorship, gold for research careers.
• Exposure to responsible AI practices at the frontier.
• A credential that opens doors across every AI lab and graduate program.

• Watch the DeepMind careers page, where student researcher and internship openings typically post in early autumn for the following year and close when filled.
• Apply with a research CV, publications or project links and a statement of research interests.
• Name specific DeepMind teams or papers that align with your work to sharpen the application.
• Interviews cover ML depth, coding and research discussions with prospective hosts.
• Offers match candidates to teams over the winter.
• Unsuccessful candidates should strengthen publications and reapply, since bars shift with cohort needs.