Postdoctoral Researcher for Data Analysis and Machine Learning of Multimodal Biomedical Data (m/f/d


The Hospital of the University of Munich, Germany, is one of the largest and most competitive university hospitals in Germany and Europe. 48 specialized hospitals, departments and institutions harbouring excellent research and education provide patient care at the highest medical level with around 11.000 employees.


Scope of duties

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.

Our requirements

PhD degree in a relevant field (computational biology or neurosciences, computer science, mathematics, or similar)

experience in analysis of complex (multimodal / high dimensional) data

strong interest in neuroscience and applying data analysis and machine learning for researching disease mechanisms or improving diagnostic procedures

previous experience in biomedial data analysis (histology, MRI, patient data, etc) or (spatial) omics data (scRNAseq, visium, MERFISH, etc) is preferred

familiar with concepts of machine learning (ML) and deep learning (DL); previous experience in applied ML / DL research is a plus

strong programming skills in Python or R collaborative and self-motivated

Our offer

We provide a highly collaborative and inspiring research environment. The lab is located in the brand-new Center for Stroke and Dementia Research building (CSD) with access to cutting-edge technologies in genomics, proteomics, metabolomics, immunology, molecular biology, imaging (from nano- to macroscale), and neuroscience in general. We are embedded within the vibrant biomedical and data science research landscape in Munich, with strong ties to the Computational Health Center in Helmholtz Munich, and with ample opportunities for local and international collaborations.

Remuneration is based on the Collective Agreement for the Public Sector of the Länder (TV-L) including all allowances customary in the public sector. The position is limited to 2-3 years.

We look forward to receiving your application consisting of a cover letter and a CV and at least two references or reference letters.

Offers and services of the employer


Application format

Please use the Online-Form for your application

Disabled persons will be preferentially considered in case of equal qualification. Presentation costs cannot be refunded.

Please note that we cannot reimburse travel expenses incurred through interviews.

Klinikum / Ludwig-Maximilians-Universität München - LMU

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No deadline
Location: Germany, Munich, München, Bayern
Categories: Biomedical Sciences, Computational Biology, Computer Sciences, Data analysis, Machine Learning, Mathematics, Neurosciences, PhD, Postdoc,


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