This project aims to develop computational methods for antigen-specific profiling of immune receptor repertoires using in silico techniques. Immune receptors play a critical role in health and autoimmunity, responding specifically to antigens from infections and vaccinations.

Since generating antigen-specific data is costly, the project will use machine learning (ML) to predict antigen specificity from immune receptor sequences.

The goals are to develop ML methods for immune receptor-antigen binding, annotate public immune receptor data with antigen information, and analyze antigen specificity variation across individuals to understand population-level diversity.

This project will be primarily hosted at the University of Oslo with Victor, and secondments are planned with Klaus in Aarhus and Linda in Amsterdam.

You can find out more about Victor’s research here: https://greifflab.org/