BioCoder (Machine Learning) | GenomeWeb

BioCoder (Machine Learning)

Desktop Genetics
Job Location
United Kingdom
Job Description

Biocoders apply their knowledge of Biology and Computer Science to build Desktop Genetic's underlying technology platform and push the boundaries of genome editing. As a member of Desktop Genetics development team, you will be tasked with applying statistical learning techniques to various biological problems.  You're results will be published at conferences and trade shows and used by thousands of scientists around the world to perform genome editing experiments.



  • Fluency in Python , common packages, and its tool chain (pdb, pytest, etc)
  • Proficiency with SciPy, Numpy, Scikit Learn, and similar technical computing frameworks
  • Proficiency with Git and GitHub-centric workflows
  • Familiarity with C and Python C extensions
  • Familiarity with PostgreSQL


Scientific Skills

  • Experience in Machine Learning, Statistical Learning, Artificial Intelligence, and similar disciplines
  • Strong knowledge of Molecular Biology and Biochemistry; Genomics experience preferred
  • Excellent quantitative skills and proven ability to apply mathematics to solve complex problems
  • Experience analyzing next-generation sequencing data sets preferred
About Our Organization

We develop technologies at the intersection of biotechnology, software and laboratory automation. We are a team of geneticists, molecular biologists, engineers and computer scientists. Together, we've developed the DESKGEN platform, an intuitive and powerful system that supports the next generation of biological research: genome editing. This platform helps scientists be more efficient in the lab by optimising the design, construction, management, and purchase of the DNA, reagents and services important in gene editing and molecular biology. Through our platform, we aim to enable “literal Desktop Genetics”, a process that researchers can use to design CRISPR gene editing experiments, purchase reagents and find commercial entities to execute those experiments - and obtain results - without them having their own specialist laboratories. To this end, we are partnering with several leading suppliers and third party vendors to offer research tools and custom CRISPR libraries for on-demand cell line engineering.

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