Postdoctoral Researcher in AI for Single-cell Epigenomics (m/f/d)

Postdoctoral Researcher in AI for Single-cell Epigenomics (m/f/d)

Arbeitsort: Berlin

We are looking for a highly motivated postdoctoral researcher to join the Computational and Developmental Biology group at the Max Delbrück Center for Molecular Medicine (MDC) in Berlin. Our interdisciplinary team develops innovative computational approaches to reconstruct tissue trajectories from multimodal single‑cell and spatial omics data and to uncover the regulatory mechanisms driving cellular differentiation during vertebrate embryonic development. In this project, you will develop quantitative machine learning models to study how different layers of epigenetic regulation shape cell fate decisions.

During your daily work, you will:

• develop sequence‑to‑function deep learning models (e.g. Borzoi-, Enformer-, or AlphaGenome-style) to predict single‑cell chromatin accessibility, histone modifications, higher‑order chromatin organization, and gene expression in mouse and zebrafish embryos
• design and perform large‑scale in silico perturbation experiments, including motif ablation, virtual transcription factor knock‑outs, and regulatory‑element screening, to generate mechanistic hypotheses
• analyse experimental perturbation datasets from in‑house projects and collaborations, including perturbations of histone modifiers and developmental signalling pathways such as Nodal, BMP, FGF, WNT, and retinoic acid
• compare mouse and zebrafish embryogenesis to identify conserved and species‑specific regulatory programs
• collaborate closely with experimental researchers to design validation experiments and refine predictive models
• contribute actively to a highly interdisciplinary and collaborative environment of computational and experimental biologists

PhD (or MSc with several years of working experience) in computational or natural sciences with a strong computational / quantitative focus

Strong programming skills in Python or R; experience with a modern deep‑learning framework; experience in building efficient and reusable software is a plus

Solid background in machine learning

Experience with the analysis of high‑throughput sequencing data (single‑cell RNA‑seq, ATAC‑seq, multiome) is highly desirable

Ability to work both independently and collaboratively in an interdisciplinary team

You also benefit from:

• a remuneration in accordance with the collective agreement for the federal public service (TVöD-Bund), including additional company pension schemes
• flexible working hours and childcare support
• the possibility of mobile working
• an idyllic green campus, which is easily accessible by bicycle, public transport or car
• free use of Nextbike from the Buch S-Bahn station to the campus
• subsidy for the job ticket as well as discounts in the campus canteen
• on‑campus health and fitness center
• additional health benefits such as flu vaccination, eye test, ergonomics advice at the workplace