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Bioinformatician, LabGenius, London, UK

LabGenius is the first biopharmaceutical company developing next generation protein therapeutics using a machine learning-driven evolution engine (EVA™️).

Our protein engineering platform integrates several bleeding edge technologies from the fields of machine learning, synthetic biology, and robotics. We use advanced deep-learning neural networks to explore protein fitness landscapes and improve multiple drug properties simultaneously.

We are a London-based, privately-owned company, backed by top-tier venture capital funds.


We’re looking for a Bioinformatician to play a critical role in building our cutting-edge platform to discover revolutionary medicines using machine learning.

What you’ll do in this role.

  • You’ll be interacting daily with a variety of disciplines, using your expertise in NGS data analysis to help drive important projects and discussions.
  • You’ll analyse NGS data generated by our in-house wet lab team, then discuss the results with the wider R&D team to draw conclusions.
  • You’ll collaborate with NGS and Data Science to develop relevant pipelines to analyse barcode/UMI containing libraries. Together, you’ll plan follow-up experiments when needed.
  • You’ll also develop and maintain sequence analysis tools with the Software team, plus research literature for cutting edge approaches / new datasets.
  • From designing experiments with wet-lab scientists, to providing them with constructive feedback, your ability to distil complexity into concise communications will be put to use every day!


What we’re looking for from you.

  • You’ve collaborated with wet lab scientists to plan and execute multiple experiments with diverse sequence repertoires (e.g. T-cell receptor, antibodies, or protein engineering using in vitro-generated libraries). You’re used to giving feedback when there are issues with the data.
  • You have a biomedical science background, which helps you understand what goes down in the wet lab and therefore plan and design experiments effectively.
  • You’ve developed custom pipelines for analysis of NGS data from variant libraries for projects that did not follow standard published procedures. Analysing amplicon-based data will take up a lot of your time so you need to both enjoy and excel at it.
  • You’re expert in Python, solid on applied statistics, and have a broad knowledge of bioinformatics tools and databases.



Anissa Cooke

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