Requirements:

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).

Nice to haves:

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.

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.

Opportunity to work at Google DeepMind in London, UK.
Engage in cutting-edge research at the intersection of AI and biosecurity.
Collaborate with a diverse team of researchers and engineers on impactful projects.
Contribute to global AI development efforts with a focus on safety and ethics.