Computational microbiomics and Systems Biology of Fungal Infections

This research area develops mathematical and AI-driven computational models to understand infection dynamics within complex host–pathogen–microbiome–immune interactions. It integrates pathobiome analysis with predictive modeling to design targeted interventions, including microbiome-informed diets and synthetic microbial communities.

The Department Microbiome Dynamics (MBD) contributes, using computational methods, to the development of personalized microbiome-based strategies to aid in the detection, monitoring, treatment, and prevention of human diseases. MBD is currently coordinating the EU-funded consortium MiCCrobioTAckle, the BMFTR-funded consortium PerMICCion, and is an active participant in the EU-funded consortia FOODGUARD (www.foodguard-project.eu/) and NUTRIMMUNE, the Cluster of Excellence "Balance of the Microverse" funded by the Deutsche Forschungsgemeinschaft, and the consortium SynThera funded by the Carl Zeiss Foundation.

A key component of the MBD research involves the computational integration of multi-omics datasets from both microbial communities and the host, with the goal of uncovering the systemic impact of gut bacteria on human physiology.  We work at the interface of the gut microbiome, diet, and the immune system to investigate the role of gut bacteria in various diseases, including but not limited to cancer, metabolic disorders, ageing, and infections.

We are seeking an excellent and enthusiastic postdoctoral researcher with a strong interest in computational microbiome research. The specific focus of the project 'should align with the objectives of the aforementioned consortia.

Your profile:

• PhD degree in Computational Biology, Bioinformatics, Systems Biology, Bioengineering, Chemical Engineering, or a related discipline
• Knowledge and experience in the analysis of metagenomics, untargeted metabolomics, or other biological high-throughput datasets
• Knowledge of statistical methods in the context of biological systems
• Experience with programming (Python, Perl, C++, R)

The Department Applied Systems Biology (ASB) contributes to the development of image-based systems biology approaches aiding in the detection, monitoring, treatment, and prevention of infections by human-pathogenic fungi. ASB is currently an active participant in various initiatives funded by the German Research Foundation (DFG), such as the collaborative research center PolyTarget 1278 – "Polymer-based nanoparticle libraries for targeted anti-inflammatory strategies", the research training group M-M-M 2723 - "Materials-Microbes-Microenvironments", the National Research Data Management initiative NFDI4Bioimage, and the Cluster of Excellence Balance of the Microverse, as well as the Leibniz Center for Photonics in Infection Research funded by the Federal Ministry of Research, Technology, and Space (BMFTR).

A key component of the ASB research involves all aspects of the Image-based Systems Biology approach. This modern computational approach comprises the automated analysis of microscopy and/or spectroscopy data based on state-of-the-art methods from machine learning, including artificial intelligence, as well as the computer simulation of mathematical models using advanced spatiotemporal approaches in experiment-driven interdisciplinary studies. The specific focus of the project 'should align with the objectives of the aforementioned consortia.

Your profile:

• Doctoral degree in Bioinformatics, Computational Biology, Computer Science, Physics, Systems Biology, or a related discipline
• Strong interest in biological systems and an educational background in biology are preferred
• Experience in mathematical modeling and computer simulations and/or modern image analysis approaches
• Very good programming skills, preferably in C/C++ and/or Python