Postdoc in Bioinformatics / Computational Biology (all genders) - The Department of Nephrology and Else Kroener-Fresenius Center


Anstellungsart: limited contract

Arbeitsmodell: full time

Ausschreibungsnummer: 2148486



Die Universitätsmedizin Frankfurt gehört zu den führenden Universitätskliniken in Deutschland. Bei uns ziehen über 8.500 Menschen aus über 100 Nationen an einem Strang. Aus Wissen wird Gesundheit - das ist dabei unser täglicher Antrieb. Denn wir verbinden Krankenversorgung mit Forschung und Lehre, begrüßen den Fortschritt und entwickeln uns selbst immer weiter. So leisten wir einen wichtigen Beitrag für die Gesundheit und die Lebensqualität von über 500.000 Patientinnen und Patienten jährlich: kompetent, gewissenhaft und mit Leidenschaft.
The Department of Nephrology and Else Kroener-Fresenius Center provides excellent facilities to conduct interdisciplinary research in the field of Nephrology and Cardiovascular biology. We offer an attractive surrounding for modern science in molecular medicine, systems biology, and data science.
It is embedded in the excellence cluster Cardio-Pulmonary Institute (CPI), the Deutsche Zentrum für Herz-Kreislauf-Forschung (DZHK), and the CRC TRR 219 and provides access to state-of-the-art omics platforms, high-performance computing infrastructure, and comprehensive training opportunities.


If you have finished your PhD and if you are highly motivated to contribute to the understanding of the mechanisms leading cardiovascular disease in patients with kidney injury, apply now at the Department of Nephrology and the Else Kroener-Fresenius Center for Nephrological Research!


Your Role:


We aim to study the role of the hematopoietic system as a hub between cardiovascular and kidney diseases by leveraging large-scale multi-omics and clinical data. You will work at the interface of single-cell omics, spatial transcriptomics, AI-based modeling, and population-scale datasets to identify mechanisms driving cardiovascular complications in kidney disease.



Analysis and integration of single-cell RNA-seq (scRNA-seq), single-cell ATAC-seq (scATAC-seq), and spatial transcriptomics datasets
Development and application of AI- / machine-learning-based models (e.g., deep learning, representation learning) to dissect cellular states, trajectories, and regulatory networks
Integration of large-scale population and biobank datasets (e.g., UK Biobank) with multi-omics data to identify risk profiles, molecular signatures, and causal pathways
Close collaboration with experimental and clinical researchers to generate and test mechanistic hypotheses
Preparation of scientific manuscripts and presentation of results at national and international conferences
Contribution to supervision and mentoring of students (Master / PhD) in the field of bioinformatics and computational biology

PhD (or equivalent) in bioinformatics, computational biology, computer science, statistics, systems biology, medical data science, or a related quantitative field
Strong interest in cardiovascular and kidney diseases, translational research, and precision medicine
Proven track record in bioinformatics / data science (e.g., publications, preprints, software, or analysis pipelines)
Solid experience with analysis of NGS data, ideally including one or more of:

scRNA-seq
scATAC-seq
spatial transcriptomics


Strong programming skills in R and/or Python and experience with common bioinformatics and ML frameworks (e.g., Bioconductor, Scanpy, PyTorch, TensorFlow)
Very good knowledge of statistics and machine learning; experience with deep learning or probabilistic modeling is an advantage
Experience with large-scale data handling (HPC environments, cloud computing, containers, workflow managers)
Very good command of English (spoken and written); German is an asset but not mandatory
You are organized, team-oriented, proactive, open-minded and have good communication skills
Due to legal regulations, ...