Research Scientist, Protein Design, DeepMind

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer various learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Apply generative machine learning models to design proteins with novel functions, such as enzymes, for wet-lab testing.
Build models and procedures for making in silico predictions of the functions of designed proteins.
Resolve design failures by applying domain knowledge of protein design tools and sequence-structure-function relationships.
Collaborate with teammates from various scientific backgrounds to improve and expand the capabilities of protein design tools.
Identify high-impact research directions in protein design method development and applications.

Minimum qualifications:

PhD in a relevant field (Protein Design/Engineering, Machine Learning, Structural Biology, or similar) or equivalent practical experience.

2 years of experience using and developing protein design tools.

Experience in an application area of protein design or protein engineering.

Experience analyzing wet-lab measurements of protein function.

Preferred qualifications:

2 years of post-PhD research experience.

Experience in any of the following: mechanistic enzymology, biocatalysis, computational chemistry.

Experience performing experiments to characterize protein function.

Excellent computational, quantitative reasoning, and technical communication skills.

PhD in a relevant field (Protein Design/Engineering, Machine Learning, Structural Biology, or similar) or equivalent practical experience.

2 years of experience using and developing protein design tools.

Experience in an application area of protein design or protein engineering.

Experience analyzing wet-lab measurements of protein function.