Research Scientist, Science

Key Skills

Deep Learning, Large Language Models - LLMs, Machine learning techniques

Job Description

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.

About us

Founded in 2010, Google DeepMind’s mission is to solve intelligence and then use it to make the world a better place.

We've created a unique environment where long-term ambitious research can flourish. Our interdisciplinary team combines the best techniques from deep learning, reinforcement learning and systems neuroscience to build powerful general-purpose learning algorithms. We have already made a number of high-profile breakthroughs towards building artificial general intelligence, and we now have all the ingredients in place to make significant progress over the coming years!

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. 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, 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. 

The role

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 natural science programs. Domains may include but are not limited to: genomics, systems biology, structural biology, synthetic biology, medicinal chemistry, quantum chemistry and molecular property prediction.

Key responsibilities:

• 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 natural 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.

Minimum qualifications

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

Preferred qualifications

• Experience in applying machine learning techniques to problems in the natural sciences.
• Demonstrated success in delivering high quality research impact.
• Experience with Large Language Models and Evaluation.
• A real passion for AI!