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

The Institut für Schlaganfall- und Demenzforschung on the Campus Großhadern invites applications for the department AG Spitzer on the next possible date, in full time, for a Postdoctoral Researcher for Data Analysis and Machine Learning of Multimodal Biomedical Data (m/f/d).

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 morpholgy 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 establish strong collaborations with experimental partners at the ISD and methodological partners at the Computational Health Center at Helmholtz Munich.
- Beyond focusing 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 the analysis of complex data (multimodal / high dimensional)
- Strong interest in neuroscience and the application of data analysis and machine learning for researching disease mechanisms or improving diagnostic procedures
- Previous experience in biomedical data analysis (histology, MRI, patient data, etc.) or (spatial) omics data (scRNAseq, visium, MERFISH, etc.) 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.
- We offer further education and training, a company pension scheme, childcare services, mobile work (if suitable), a job ticket, discounts and staff accommodation (if available).
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 two to three years.

Disabled persons will be preferentially considered in case of equal qualification. Presentation costs cannot be refunded. Please send a cover letter, a CV, and any letters of recommendation as a single pdf file. For further information please contact Dr. Hannah Spitzer, phone +49 89 4400 - 46173.