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. 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. 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 Laboratory Research Scientist working on Protein Design, you will play a key role in developing and validating cutting-edge AI tools for creating proteins with novel functions, with an emphasis on enzyme catalysis. You will apply your deep practical expertise in enzymology and biochemistry to develop and execute assays to validate proteins designed by machine learning models, at our research laboratory at The Francis Crick institute. Additionally, you will use your understanding of enzyme structure and mechanism, in collaboration with machine learning experts, to troubleshoot and improve design methods. Finally, you will advise on and develop ambitious new research goals in enzyme design and engineering, as well as biomolecular modelling more generally.

Key responsibilities:

  • Design, optimise, and perform experiments to characterise the functions of novel enzymes and other proteins designed by machine learning models.
  • Train teammates in laboratory techniques.
  • Work collaboratively with teammates from diverse scientific backgrounds to improve and expand the capabilities of protein design tools.
  • Report and present research findings and developments including status and results clearly and efficiently both internally and externally, verbally and in writing, in a fast paced environment.
  • Work with external partners and maintain relationships with relevant research labs and key stakeholders as appropriate.
  • Maintain high quality electronic experimental records and contribute to maintenance of the wet lab space and operation.

 

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 field (protein design/engineering, biochemistry, structural biology, or similar) or 5+ years equivalent experience in industry.
  • Expertise in mechanistic enzymology or biocatalysis.
  • Hands-on experience developing and running assays for enzyme activity (e.g. colorimetric, fluorescence, mass spectrometric, etc).
  • Hands-on experience developing and running assays for biophysical protein properties (e.g. stability, oligomeric state, structure, etc).
  • Ability to independently troubleshoot and implement research projects.
  • High attention to detail and demonstrated persistence in troubleshooting and producing high quality data.
  • Skilled in teamwork and collaboration with computational and experimental researchers.

In addition, the following would be an advantage: 

  • 2-3 years of post-PhD research experience.
  • Expertise in any of: computational protein design, computational chemistry, machine learning, high-throughput assay development, or laboratory automation.
  • Ability to write code to perform custom data analyses.
  • A passion for AI and protein design!

Application deadline: Wednesday 27th November at 5pm GMT

 

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