Postdoctoral Researcher (d/w/m) in Population ‘omics and Pharmacoepidemiology

Postdoctoral Researcher (d/w/m) in Population omics and Pharmacoepidemiology

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Arbeitszeit

Vollzeit, Teilzeit

Eintrittsdatum

01.07.2026

Dauer der Anstellung

Befristet

Bewerbungsfrist

27.05.2026

Einsatzort Charité

BIH Berlin Mitte

Kennziffer

7102

Entgeltgruppe

E13

Company description

The Berlin Institute of Health at Charité (BIH) is dedicated to biomedical translation. Its mission is to translate research findings into personalized prevention, diagnostics, and therapies to benefit patients and provide the scientific community with effective tools. With approximately 750 employees, the BIH specializes in translational method development, precision medicine, regenerative therapies, and biomedical data science. Closely integrated with Charité, the BIH promotes excellent research and facilitates the accelerated transfer of new discoveries into clinical practice through its supporting platforms and programs. Through these efforts, the BIH builds strong partnerships and fosters innovation-driven medicine in both national and international contexts.

For the Health Data Modelling group ( we are looking for a Postdoctoral Researcher (d/w/m) in full-time or part-time (min. 30h/week) limited until 28.02.2029, starting as soon as possible. This position is funded by the ERC Starting Grant “GenDrug”, which aims to integrate large-scale genomic and real-world clinical data to discover new drug targets.

We are seeking a dedicated and rigorous researcher with a demonstrable track record in population-level multi-omics analysis, statistical genomics, and pharmacoepidemiology. The successful candidate will lead the development and publication of computational strategies that integrate multiple (blood) omics layers to guide personalized treatment decisions, i.e., understanding drug efficacy and adverse effects, and biomarker-informed drug repurposing. We are looking for applicants with a strong translational focus and clinically/biologically oriented mind set, tailoring computational approaches to urgent clinical needs. This is a fantastic opportunity for individuals with a keen interest in interdisciplinary work with a strong methodological background.

What you can expect

Analyze (blood-based) omics data (genomics, proteomics, metabolomics) from large cohorts such as UK Biobank as well as tightly defined drug intervention studies to systematically study systemic effects of novel and approved treatments.

Investigate the effects of medications on blood biomarkers and clinical outcomes, incorporating pharmacogenetic analyses.

Develop and apply statistical and computational methods (including causal inference and machine learning) to link multi-omic variation with drug response and disease phenotypes.

Build and maintain high-throughput analysis pipelines and computational infrastructure using R (and Python), and work in HPC/cloud environments.

Create interactive data visualization tools (e.g. R Shiny apps) to facilitate exploration of results.

Prepare scientific publications and figures, and present findings at conferences and seminars.

Integrate individual level data analysis with publicly available results and databases through, among others, genome-wide meta-analysis or knowledge graph integration.

Supervise and mentor junior researchers and students in data analysis projects.

What you bring along

PhD in genomics, statistical genomics, genetic epidemiology or a closely related discipline

Stage-appropriate track-record of high-impact research and publications in the field of genomics, multiomics, and/or pharmacoepidemiology