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.
Design and implement novel algorithms and machine-learning (ML) methods to address core biosecurity research questions.
Contribute to pioneering research on AI and biosecurity, supporting scientific publications and product development aligned with the Biosecurity initiative mission.
Collaborate with research scientists and engineers across the initiative and Science and Strategic Initiatives unit to prototype, experiment, and scale AI research using software engineering best practices.
Contribute to the design of biological datasets, evaluation methodologies, and infrastructure required to pursue novel research hypotheses.
Synthesize complex research findings into clear, actionable reports and presentations for both technical and non-technical stakeholders, delivered through written documentation and verbal briefings.
Minimum qualifications
Bachelor’s degree in Computer Science, Machine Learning, Computational Biology, or a related field, or equivalent practical experience.
2 years of experience with machine learning algorithms and tools (e.g., TensorFlow, Pytorch).
Preferred qualifications
PhD degree in Computer Science, Machine Learning, Computational Biology, or a related field, or equivalent practical experience.
Experience applying deep learning models to biological data (such as functional genomics or protein sequence data).
Experience working with life science data, such as in bioinformatics or health informatics.
Familiarity with emerging topics in biosecurity, such as metagenomic surveillance, de novo pathogen design, and LLM-based uplift.
Ability to identify, breakdown, and solve ambiguous and complex process and technical problems that span across many teams and organizations.
Bachelor’s degree in Computer Science, Machine Learning, Computational Biology, or a related field, or equivalent practical experience.
2 years of experience with machine learning algorithms and tools (e.g., TensorFlow, Pytorch).
