Postdoctoral fellow bioinformatics – single-cell sequencing analysis

Acute myeloid leukemia (AML) is a highly heterogeneous disease with poor clinical outcomes. Therapy resistance arises from complex interactions between genetic and non-genetic factors that are not yet fully understood.

This project combines single-cell multi-omics (RNA, ATAC and protein) with single-cell long-read sequencing to genotype individual cells. This approach enables the study of clonal dynamics and cellular plasticity at unprecedented resolution.

You will contribute to both computational method development and biological data analysis, with the goal of generating new insights into therapy resistance in AML.

You will work at the interface of computational method development, pipeline engineering, and translational cancer research, with a focus on understanding therapy resistance in acute myeloid leukemia (AML).

Your tasks include:

• developing, optimizing, and maintaining reproducible computational pipelines for single-cell long-read data (e.g. improving or extending tools such as FLAMES or related frameworks);
• designing analytical strategies to genotype individual cells and study clonal dynamics in longitudinal AML samples;
• integrating single-cell multi-omics datasets, including scRNA-seq, scATAC-seq and CITE-seq to study mechanisms of therapy resistance;
• ensuring pipelines are robust, well-documented, and accessible for other researchers;
• translating complex datasets into biological insights in collaboration with experimental scientists.

You are a computational scientist with a strong interest in biology and enjoy working in a collaborative research environment. You combine technical expertise with analytical thinking and clear communication.

You bring:

• a PhD (or near completion) in bioinformatics, computational biology, computer science, statistics, or a related field;
• strong programming skills in Python and/or R;
• experience with single-cell genomics data analysis, such as scRNA-seq, scATAC-seq or multiome data;
• experience with workflow management systems (e.g. Nextflow, Snakemake or WDL) and version control (Git);
• strong communication, presentation, and scientific writing skills, and the ability to work both independently and collaboratively.

Experience with long-read sequencing, isoform analysis, variant calling, or scalable computing environments is considered an advantage.