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Snapshot
Science is at the heart of everything we do at Google DeepMind. From the beginning, we took inspiration from science to build better algorithms, and now, we want to use our toolkit to accelerate scientific discovery. By bringing together specialists with backgrounds in machine learning, computer science, physics, chemistry, biology and more, we’re optimistic that we can build new methods that will push the boundaries of what is possible and help solve the biggest problems facing humanity.
About the Biosecurity Function
Projects like AlphaFold, where we're leveraging AI to help get us closer to predicting the shape of proteins, and AlphaProteo and AlphaMissense, are some examples of our work towards this mission. We are dedicated to proactively identifying and responsibly addressing potential biosecurity risks associated with our technologies, and taking steps to encourage our models to help improve biosecurity, where possible. We define biosecurity as protection against high-impact biological risks, including those that arise naturally, accidentally, or through intentional misuse.
About Us
Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
The Role
As a Research Scientist working on Biosecurity, you will play a crucial role in ensuring the responsible development and deployment of cutting-edge AI technologies for biological applications. You will apply your deep understanding of biology, in areas like virology, bioinformatics, infectious diseases and emerging biosecurity topics like biological threat and pathogen surveillance, coupled with knowledge of protein structure and sequence analysis, to anticipate potential misuse scenarios of AI x biology models. You will contribute to shaping our biosecurity strategy by conducting in-depth risk assessments, developing mitigation strategies, and contributing towards our culture of responsible innovation within the Science unit.
Key responsibilities:
- Proactive Biosecurity Risks and Benefits Assessment: Undertake exploratory analysis to inform research directions in biosecurity, understanding AI x biology model capabilities, thinking critically about how these capabilities could lead to both biosecurity benefits and potential harms.
- Mitigation Development: Research, design and implement technical and policy-based mitigation strategies to address identified biosecurity risks, collaborating with research, engineering, and policy teams, while exploring steps that could improve the benefits of our models to biosecurity.
- Threat Modeling: Develop and refine threat models specific to Biological AI tools and technologies, anticipating potential future risks and vulnerabilities.
- Biosecurity Research: Contribute to pioneering research on AI and biosecurity topics, exploring areas like novel mitigation techniques, misuse case development, and threat modelling.
- Community Engagement: Engage with the broader biosecurity community by participating in conferences, workshops, and public policy discussions, fostering collaboration and sharing best practices.
- Research collaboration: Collaborate with researchers and machine learning engineers to identify and develop novel machine learning approaches tailored to the sciences.
About You
In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:
- PhD in a relevant biological field (e.g., virology, microbiology, infectious diseases) with demonstrated experience in protein structure and sequence analysis.
- Passion for accelerating science using innovative technologies.
- Good understanding of and interest in biosecurity and biosafety concepts and principles.
- Ability to think critically and creatively about potential misuse scenarios of emerging technologies.
- Motivated by understanding and keeping up with biosecurity risks, concepts, policy approaches and how AI may affect them and passionate about engaging with other types of practitioners that contribute to biosecurity discussions, and understanding diverging views.
In addition, the following would be an advantage:
- Experience in policy analysis or development related to biosecurity or emerging technologies.
- Familiarity with machine learning concepts and techniques.
- Experience with bioinformatics tools and databases.
Application deadline: Wednesday 2nd October at 5pm BST.