· The ideal candidate should hold a PhD degree in bioinformatics or related fields. · The candidate should have extensive experience in programming (e.g. R, Python, Matlab), the analyses of omics data (with a particular focus on proteomics and metabolomics) and (ideally) of longitudinal data. · Specifically, the candidate would benefit from experience in using MaxQuant and Perseus and in the application of machine learning methods, mixed models, clustering techniques, sinusoidal regression, and regression splines. · Medical background and knowledge of biochemical processes is a plus. · Suitable candidates should be highly motivated, have a high-degree of technical expertise, problem solving skills and scientific independence, with an interest in bioinformatics and methods development in a clinically oriented research setting.