Postdoctoral Fellow (f/m/x)
Core
Reconstruct clonal and subclonal architecture of chronic lymphocytic leukemia (CLL) and track its evolution under targeted therapies using bulk and single-cell sequencing data.
Role type
Postdoctoral Fellow in Computational Cancer Evolution
Builds
Computational methods for evolutionary principles integrated with genomic, transcriptomic, and spatial data linked to clinical outcomes
Domain
Oncology / Bioinformatics / Computational Biology
Deliverable
production ML models
Required skills
Clonal deconvolution, phylogenetic inference, mutational signatures analysis, copy-number and structural variant analysis, single-cell DNA/RNA sequencing analysis, Python, R, reproducible workflows (Snakemake, Nextflow), high-performance computing
Preferred skills
Longitudinal or clinical trial data analysis, haematological malignancies expertise
Technologies
Python, R, Snakemake, Nextflow
Responsibilities
Reconstruct tumour phylogenies and quantify intratumour heterogeneity, identify evolutionary trajectories leading to treatment resistance and relapse, develop and apply computational methods, integrate multimodal data with clinical outcomes, lead independent projects, co-supervise PhD and Master students
Seniority
Postdoctoral Fellow, independent researcher with mentorship duties