At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

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. Projects like AlphaFold, where we're leveraging AI to help get us closer to predicting the shape of proteins, show the promise of this approach. 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.

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.

As a Research Scientist in the Science Program, you will use your machine learning expertise to collaborate with domain experts and other machine learning scientists within our computational  science programs. Domains may include but are not limited to: algorithm discovery, computational complexity theory, quantum computation, information theory, applied and pure mathematics.

• Engage with existing research efforts in the Science Program to solve key challenges using your broad machine learning experience.
• Collaborate with researchers and machine learning engineers to identify and develop novel machine learning approaches tailored to the sciences.
• Report and present research findings and developments (including status and results) clearly and efficiently both internally and externally, verbally and in writing.
• Suggest and engage in team collaborations to meet research goals for the wider science programme.

In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:

• PhD demonstrating significant advances in machine learning or equivalent practical experience.
• Passion for accelerating science using innovative technologies.
• Programming experience.
• Quantitative skills in math and statistics.
• Experience of common scripting languages or pipelining tools.

In addition, the following would be an advantage: 

• Experience in applying machine learning techniques to problems in computational or mathematical sciences.
• Broad expertise in theoretical computer science, in particular algorithms and complexity theory.
• Demonstrated success in delivering high quality research impact.
• Experience with using Large Language Models in automated loops.
• A real passion for AI!

Application Deadline: Tuesday 14th May at 5pm BST