Description
You develop data engineering pipelines and analytical tools to interpret large-scale DNA-encoded library screening data, supporting small-molecule drug discovery.
Tasks
- Apply statistical methods and predictive models to interpret large-scale DEL screening datasets
- Develop analytical tools and workflows for screening scientists to prioritise compounds
- Design and maintain automated, reproducible data processing and analysis pipelines
- Develop computational workflows and searchable building-block data resources
- Partner with experimental scientists, computational chemists and machine learning teams
- Present analytical results and technical developments to multidisciplinary audiences
- Promote reproducibility, data integrity and robust engineering practices
Profile
- PhD or M.S. in Bioinformatics, Statistics, Computer Science, Data Science, Cheminformatics, Software Engineering or related field
- Strong software engineering background deploying pipelines at scale in HPC or cloud platforms
- Experience in high-throughput scientific data analysis, DEL selection outputs or NGS processing pipelines
- Strong proficiency in Python and statistical programming
- Expertise in data visualisation frameworks such as Spotfire or Tableau
- Experience with cheminformatics toolkits and laboratory data systems (LIMS, SQL, relational databases)
Company
Pharmaceutical research