Postdoctoral Researcher for Data Analysis and Machine Learning of Multimodal Biomedical Dat (m/w/d)

· We are looking for a postdoc to join the growing team of the machine learning and data analysis group at the Institute for Stroke and Dementia Research (ISD). · Our group uses computational analysis and machine learning algorithms to identify patterns and relationships from complex, multimodal, and multiscale datasets of the brain in health and disease, with a primary focus on neurovascular and neurodegenerative phenotypes. · Within this context, you will work on predictive and generative methods to extract disease-relevant information from multimodal omics, spatial omics, and imaging datasets. · For example, we aim to use MERFISH, histology, and MRI data, to study how gene expression correlates with morhpolgy and what differentiates healthy from diseased tissues by employing supervised, self-supervised and unsupervised machine learning algorithms and novel spatial omics data analysis methods. · For this, you will leverage and build up strong collaborations with experimental partners at the ISD and methodological partners at the Computational Health Center in Helmholtz Munich. · Beyond focussing on your research projects, you will also be expected to contribute to the development of a pipeline for analysing spatial omics and other biomedical data.