We are looking for a postdoctoral researcher in multimodal omics and image analysis to join our growing team in the Omics Analysis and Integration (Omics A&I) Hub of SyNergy and the Spitzer lab) at the Institute for Stroke and Dementia Research (ISD).

About us

The Cluster of Excellence SyNergy (Munich Cluster for Systems Neurology) investigates how complex neurological diseases such as Alzheimer's and Parkinson's Disease, stroke, or multiple sclerosis develop. Using systems neurology as a new interdisciplinary approach, researchers can better map the processes behind overlapping mechanisms involved in neurovascular, neurodegenerative, and neuroimmunological diseases, and develop approaches for novel therapies.

In the Spitzer lab, we integrate single-cell omics, spatial omics, histology, and neuroimaging data by developing and applying multimodal machine learning methods to better understand the brain in health and disease, ultimately aiming for more personalized diagnostics and treatments. We lead the newly established Omics A&I Hub within SyNergy, where we provide these state-of-the-art computational methods for multimodal data analysis, data integration and collaborative support to consortium members.

Your role

You will support and actively engage in collaborative projects requiring advanced omics, data integration, and multimodal analyses within the Omics A&I Hub. Working closely with bioinformaticians and researchers across SyNergy projects you will:

1. perform advanced single-cell and spatial omics analyses and integrate multi-omics and imaging data;
2. identify and adapt spatial and multimodal omics workflows to diverse datasets and disease-specific use cases;
3. leverage our association with the Computational Health Center at Helmholtz Munich to establish close collaborations with method developers.

To advance current data integration methods, you will also have the opportunity to develop novel representation learning approaches to integrate multiple layers of bulk and single-cell omics, spatial omics, and imaging data. For example, we recently developed a pipeline using optimal transport and demixing tools to extract cell-type specific lipid profiles from single-cell spatial transcriptomics and spot-based spatial lipidomics data – a framework we aim to extend to additional use-cases.

You will further collaborate with the Nanoscale (EM) and Spatial Transcriptome Hubs in SyNergy to develop cross-modal and cross-scale analysis methods linking histology, spatial omics and electron microscopy data. This integrative work will help uncover the relationships between molecular and morphological features in brain tissues.

Our requirements

• PhD degree in a relevant field (computational biology or neurosciences, computer science, mathematics, or similar)
• Strong interest in neuroscience and applying data analysis and machine learning to study disease mechanisms or improving diagnostic procedures
• Previous experience in (spatial) omics analysis (e.g. scRNAseq, proteomics, Visium, MERFISH); experience with histological data analysis is a plus
• Familiarity with machine learning and deep learning concepts; prior experience in applied ML/DL research preferred
• Strong programming skills in Python or R
• Good knowledge of Linux and HPC systems
• You are collaborative, self-motivated, and eager to work in interdisciplinary teams

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, and associated with the Computational Health Center in Helmholtz Munich, providing ample opportunities for local and international collaborations. SyNergy also offers a diverse and inclusive environment with comprehensive support for newcomers, including gender equality initiatives, mentoring, travel grants, post-doctoral awards, and family support.

How to apply

Please send your application (cover letter, CV with publication list, contact details for at least two referees or reference letters) to hannah.spitzer@med.uni-muenchen.de.

Start date: As soon as possible.

Application review: Applications will be reviewed on a rolling basis until the position is filled; early submissions are encouraged.

Contract details: The position is initially limited to 2 years with the possibility of extension.

Remuneration is based on the Collective Agreement for the Public Sector of the Länder (TV-L) including all allowances customary in the public sector.