PhD research fellow immuno-informatics in inflammatory bowel disease

Inflammatory bowel disease (IBD) constitutes a group of incurable, chronic, relapsing diseases of the gastrointestinal tract, stemming from a dysregulated interplay between the environment and the immune system in genetically susceptible individuals. Treatment typically involves suppressing inflammation, aiming to induce or maintain a state of endoscopic remission. Currently, this is accomplished through monoclonal antibodies or small molecules targeting inflammation mediators like TNF (infliximab and adalimumab), IL12/23p40 (ustekinumab), and the JAK-STAT pathway (tofacitinib and upadacitinib), or molecules involved in immune cell recruitment to the gastrointestinal tract, such as integrin α4β7 (vedolizumab). Despite the established efficacy of these biological treatments, sustained endoscopic remission is observed in fewer than a third of patients after one year of treatment. Hence, a personalized treatment is highly warranted. Previously, we identified several epigenetic biomarkers in peripheral blood capable of prognostically predicting response, which is currently funded by the Horizon Europe consortium grant entitled METHYLOMIC.

We are looking for a highly motivated applied bioinformatician who is willing to lead the bioinformatics and data analytical side of this project in understanding response to therapy. This position is funded by the aforementioned METHYLOMIC grant in combination with a local institutional grant.

The overarching aim is to personalize treatment to ensure patients are provided the most optimal care. Your primary focus will involve the analysis of existing omics datasets from IBD patients to gather insights in driving subsequent experiments. You will be working extensively with single-cell technologies and machine learning assisted analyses of epigenetic markers to identify specific cellular subsets linked with disease progression and therapy response. Accordingly, a key aspect of your work will involve leveraging both external and internal datasets to inform subsequent experiments.

We are looking for a candidate with:

• A master's degree in Biomedical Sciences, Infection & Immunity, or a related life-science field, with a strong emphasis on applied data analysis and/or machine learning;
• Prior experience in performing (in vitro) and analyzing (in silico) omics data, such as RNA-sequencing, DNA methylation microarrays. Previous exposure to single-cell omics technologies, such as single-cell RNA-sequencing, is desired;
• Proficiency in R, Python, and bash scripting, along with familiarity working in a Linux environment using schedulers, is expected;
• Previous exposure to workflow management systems like Snakemake and/or Nextflow is preferred;
• Good written and verbal communication skills in English are essential to communicate in our international team;
• You are inherently driven, scientifically curious, and adept at collaborative teamwork.

You will be collaborating with researchers at the Tytgat Institute for Liver and Intestinal Research and the Department of Gastroenterology at Amsterdam UMC. The Tytgat Institute consists of approximately 70 researchers engaged in fundamental, applied, and clinical research within the fields of gastroenterology and hepatology. While you will primarily work with colleagues at the Tytgat Institute, we actively encourage you to collaborate with peers outside the Tytgat Institute to facilitate knowledge exchange.