CATH is an internationally renowned resource providing information on sequence-structure-function
relationships for over a hundred million proteins. We are recruiting a postdoc grade 7- 8, depending on
experience. This post will develop new computational algorithms and protocols exploiting machine
learning, for better functional classification of domains in CATH. This is a collaborative project with
PDBe, UniProt, SWISS-MODEL, Rosetta, ModBase which will improve the functional classification of
CATH domains to provide templates for improved protein structure prediction and to improve functional
site prediction. The Orengo group exploits CATH data in a range of collaborations with experimental
groups researching the impacts of genetic variations (eg cancer studies, protein design to engineer
enzymes for improved plastic degradation) and the postdoc would also be able to contribute to these
projects. Expertise in website design and development would also be an advantage to present the
functional classification data intuitively to the large community exploiting this CATH data.
PhD in computer science, biological or physical science