Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive forms of cancer, with a high mortality rate. Therapies for PDAC are limited to chemotherapy, which has been ineffective to treat advanced stages of the cancer. Therefore, it is critical to identify biomarkers and develop targeted therapies, to improve early diagnosis and patient care. We have generated mass spectrometry (proteomics and phosphoproteomics) data from 15 PDAC patient-derived xenographs (PDX), which have been grown in mice. These PDX can be separated based on their response to chemotherapy. The project aim is to develop a bioinformatics pipeline to identify the proteomics-based signature differentiating chemo-resistant versus sensitive tumours. Ultimately, the data will be used to identify biomarkers and potential therapeutic targets for further evaluation. The student will use bioinformatic techniques to cluster protein expression profiles, enrichment of signalling pathways and design data visualisation approaches to dissect the complex real-life biological data.