majid tavakoli

At CECAD, University of Cologne, I developed computational workflows in Python and R to process and analyse large-scale biomedical datasets during an international research period.

I built preprocessing, analysis, and visualisation pipelines, and optimised workflows for efficient processing. I also applied machine learning techniques to analytical problems in this research environment.

For my Parkinson's disease classification project, I built a machine-learning pipeline using gait-analysis data, applied clustering to discover patterns, and evaluated model performance.

My projects also include reproducible spatial transcriptomics workflows and medical image preprocessing and feature extraction. I'm pursuing an MSc in Medical Bioinformatics at the University of Verona and am seeking a junior software or ML engineering role.