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.

I filter compound libraries using RDKit (Lipinski, ADMET), pass them to AutoDock Vina, and parse and rank the output in pandas. For molecular dynamics, I use GROMACS, post-process in MDAnalysis/MDTraj to produce RMSD/RMSF plots with matplotlib, and inspect structures in PyMOL. For publication-quality statistics, I use R/ggplot2. Connective tissue — PubChem lookups, pushes to shared sheets, database writes — is automated in n8n.

• 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.)

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 Vina, then validated the top hit with molecular dynamics and τRAMD. Aesculin ranked first in initial screening at −6.39 kcal/mol; subsequent MD/τRAMD analysis characterized it as a moderate, reversible inhibitor with a short residence time. Published: Biochemical and Biophysical Reports

Led a multi-target virtual screening campaign across three neurodegenerative targets (MAO-A, Synapsin I, Synapsin II), narrowing the field to 12 multi-target hits through pharmacophore modeling. Manuscript submitted, currently under review.

A position in Germany as a Bioinformatics Scientist, Computational Biologist, or Data Scientist in a life-science research group where computation and wet-lab work are closely linked. Available to start immediately, can attend in-person interviews, and able to relocate.

🇬🇧 English — IELTS 7.0 🇩🇪 German — A2, working toward B1/B2