At Fraunhofer ITMP, I built Python workflows for biomedical data analysis and machine learning, and evaluated and extended a DNA methylation age-prediction workflow by comparing LASSO, Elastic Net, and SVR models.
I also developed data-preprocessing and molecular-feature-generation workflows, including a Streamlit Fingerprint Feature Generator for the Fraunhofer Data Science Toolkit. I used RDKit, scikit-learn, Git, and GitHub in reproducible workflows for biomedical and target-related datasets.
At the Institute of Immunology, UKE, I developed nanobody-based therapeutic and diagnostic strategies targeting the CDT binary toxin and TcdB of Clostridioides difficile. I generated and characterized a nanobody library for toxin detection and evaluated lead candidates for diagnostic applications and neutralizing therapeutic potential.
