My background is wet-lab first — mesenchymal stem cell culture, ELISAs, the whole manual pipeline. I moved into computational work because data volumes stopped being manageable by hand. Now I build the automation that connects both sides.

My background started in wet-lab biology — mesenchymal stem cell culture, ELISAs, standard laboratory workflows. During my MSc, my research moved into molecular docking and molecular dynamics, and that shifted my long-term direction toward computational methods. I still build the automation that connects both sides.

• pubchem-metabolite-descriptor-fetcher — Python + R pipeline that batch-fetches physicochemical descriptors from PubChem and visualizes drug-likeness against Lipinski/TPSA thresholds.
• vina-docking-pipeline — Parses, filters, and ranks AutoDock Vina docking output; generates a ranked hit list and affinity chart.
• cadd-fastapi-service — FastAPI service exposing CADD pipeline stages as REST endpoints for integration with automation tools like n8n. (Active development — see repo README for current endpoint status.)
• md-trajectory-analysis — RMSD/RMSF analysis of a short GROMACS MD simulation, with PyMOL structure rendering.
• n8n-automation-examples — Webhook-triggered n8n workflow: PubChem lookup, Lipinski filtering, branching error handling, and Google Sheets logging.

Engineered human Wharton's jelly mesenchymal stem cells with a lentiviral vector to express erythropoietin (EPO) in a 4T1 breast cancer mouse model. Maintained therapeutic levels of plasma EPO, hemoglobin (Hb), and hematocrit (Hct) for over 10 weeks post-transplantation. Published: Current Gene Therapy

Docked walnut husk metabolites against pectate lyase Pel3 using AutoDock 4.2 as the primary method (AutoDock Vina 1.2 as a secondary cross-check), then validated the top hit — Aesculin — with molecular dynamics and τRAMD. MM-PBSA binding free energy ≈ -2.9 kcal/mol, average RAMD residence time ≈0.015 ns — consistent with moderate, reversible binding rather than a strong inhibitor. Published: Biochemical and Biophysical Reports

Network-Based Transcriptomics Identifies Key Hippocampal Targets in Alzheimer’s Disease and Their Modulation by Apigenin, Luteolin, and Berberine. Manuscript submitted, currently under review.

A research-oriented position — Bioinformatics Scientist, Computational Biologist, or Computational Drug Discovery Scientist — in a life-science team where computation and wet-lab work are closely linked. Primarily targeting Germany, the Netherlands, Switzerland, Denmark, Norway, and Ireland, open to strong opportunities elsewhere. Visa sponsorship needed — happy to discuss timeline directly.

English — IELTS 7.0
German — A2, working toward B1/B2