Computational biologist · Bioinformatics scientist · PhD candidate at DKFZ/KiTZ
I combine multi-omics analysis in R and Python with experimental validation to investigate cancer vulnerabilities. My work connects patient-cohort data, biological interpretation and target-discovery hypotheses, with a focus on Ewing sarcoma.
I expect to complete my PhD in October 2026 and am exploring computational biology, bioinformatics and biomedical data-science roles in Germany.
Public analysis code from my first-author doctoral project investigating chromosome 1q gain and SF3B4-associated vulnerability.
- Biological question: connect a recurrent copy-number alteration to clinical associations, molecular changes and candidate vulnerabilities.
- Methods represented: copy-number and survival analysis, differential expression, pathway enrichment, network-based driver prioritization and proteomics.
- Explore the code: topic-organized R/Python workflows, documented data-access boundaries and a small offline synthetic demo.
This is collaborative research. The repository documents manuscript authorship, and controlled patient-level and raw experimental data are not distributed publicly.
- Analysis: bulk and single-cell RNA-seq, copy-number alterations, survival analysis, pathway enrichment and multi-omics integration.
- Tools: R/Bioconductor, Python, Linux/shell and Git.
- Research: cancer genomics, biomarkers, target discovery and translating computational hypotheses into experimental follow-up.
- Experimental perspective: inducible perturbation models, flow cytometry/FACS and molecular assays.
Co-author of High 4E-BP1 expression associates with chromosome 8 gain and CDK4/6 sensitivity in Ewing sarcoma, published in the Journal of Clinical Investigation. This is a separate study from the SF3B4 project above.
Based in Darmstadt, Germany; interested in opportunities in the Frankfurt Rhine-Main/Heidelberg region and remote roles in Germany. The best place to reach me is LinkedIn.