Research Scientist, Protein Function, Science

We are hiring for this role in Cambridge (US), MTV or New York. Please clarify in the application questions which location(s) work best for you.

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.

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. 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.

About Us

Artificial Intelligence could be one of humanity’s most useful inventions. We’re a dedicated scientific community, committed to “solving intelligence” and ensuring our technology is used for widespread public benefit. We’ve built a supportive and inclusive environment where collaboration is encouraged and learning is shared freely. We don’t set limits based on what others think is possible or impossible. We drive ourselves and inspire each other to push boundaries and achieve ambitious goals.

The Role

To succeed in this role you will need to be passionate about advancing models for biological sequences using recent breakthroughs in ML/AI, together with standard machine learning and other computational techniques. You’ll join an interdisciplinary team of domain experts, ML researchers and engineers exploring a central challenge in biochemistry: the prediction of functional properties of a protein from its amino acid sequence. 

Our work is organised into several longer-term focus areas which aim to achieve step changes to the state-of-the-art. You will contribute to the knowledge and experience of the team with your own scientific domain knowledge, and will work with internal and external researchers on pioneering research bridging AI and science. You’ll leverage our unique mix of expertise, data and computational resources to experiment and iterate both rapidly and at scale.

Key responsibilities:

• Plan and perform rapid prototyping of machine learning techniques applied to problems in science, specifically biological sequence modelling.
• Undertake exploratory analysis to inform experimentation and research directions.
• 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.
• Collaborate with researchers and machine learning engineers to improve and expand capabilities of our protein function prediction models and develop novel machine learning approaches tailored to the sciences more broadly.
• Collaborate with internal and external scientific domain experts.

The role will suit candidates who enjoy working in a heavily experimental setting with large and noisy datasets and who wish to immerse themselves in innovative Science, ML and AI research.

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 demonstrating significant advances in the application of machine learning to biological challenges.
• Passion for accelerating science using innovative technologies.
• Track record demonstrating the ability to develop and execute successful research projects at the interface of ML and biology/biochemistry.
• Quantitative skills in math and statistics.
• Experience working with large and noisy datasets.
• Experience exploring, analysing and visualising data.
• 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 the biological sciences.
• Experience with setting up tasks, evaluations, datasets for measuring and improving model performance
• Broad expertise in computational biology, in particular building predictive models for biological sequences.
• Demonstrated success in delivering high quality research impact.
• Experience working with a range of ML model architectures.
• A real passion for AI!

When assessing technical background we will take a holistic view of the mix of scientific, ML and computational experience. We do not expect you to be an expert in all fields simultaneously, however, since the role serves as a bridge between all three, some experience in each is necessary.

The US base salary range for this full-time position is between $114,000 – $245,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Application Deadline: 11th March 2025