The Roche Postdoctoral Fellowship (RPF) program is aimed at supporting excellent young scientists focusing on collaborative R&D projects between Roche and international academic institutions. Both internal Roche and academic experts will mentor you, and you will have the potential to perform hands on research in both environments.
Within Roche pharma Research and Early Development (pRED), the Clinical Pharmacology department is committed to enable the selection of safe and effective dose, route and regimen for every patient by applying the principles of quantitative pharmacology throughout a molecule’s life-cycle. As a part of Clinical Pharmacology, the Disease Modeling group supports the decision making process in the respective disease therapeutic area through the development of empirical and/or mechanistically-based drug disease models which integrate disease pathophysiology, drug target information and clinical data.
In this project, you will develop and apply novel integrative machine learning framework to identify prognostic and predictive markers of outcomes measured longitudinally in rheumatoid arthritis clinical trials. This framework will be based on statistical concepts such as Bayesian hierarchical models, multi-view/multi-task machine learning methods to make use of clinical variables, biomarkers and –omics datasets (such as transcriptomics, proteomics, metabolomics and immunomics), collected at baseline.