Research Scientist, Biomedical AI, DeepMind

In this role, the team develops foundation models and AI-driven discovery systems that uncover new therapeutic strategies and generate scientific insights. This research directly shapes how we understand and treat cancer.

As a Research Scientist, you will build AI models and AI-driven discovery systems to accelerate scientific discovery for cancer treatment. You will develop and evaluate foundation models on multimodal biological and medical data, design benchmarks grounded in scientific utility, and collaborate with academic and clinical partners to drive research with real-world health impact.

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.

Responsibilities

• Design, train, and evaluate AI models and LLMs on multimodal biological and medical data.
  
• Develop computational pipelines and agentic workflows that enable researchers to generate, prioritize, and validate scientific hypotheses.
  
• Develop benchmarks and evaluation frameworks that capture scientific utility and ML performance.
  
• Work with internal and external collaborators, academic and clinical research partners on problems with real-world health impact. 
  
• Drive research from conception to publication. Report and present ideas, experimental results, and data analysis clearly and efficiently.

Minimum qualifications:

• PhD in Computer Science, a related field, or equivalent practical experience.
• One or more scientific publication submission(s) for conferences, journals, or public repositories.

Preferred qualifications:

• 2 years of coding experience.
• 1 year of experience owning and initiating research agendas.
• Experience working with biological or medical data modalities.
• Experience developing or evaluating foundation models or LLMs.
• Passion or experience with scientific research in any field of science.