Mozhdeh Davoodifard

• Processed and analysed Vis–NIR, LIBS and XRF spectral datasets for modelling soil properties. • Developed Python workflows for data preprocessing, machine learning modelling and visualization. • Integrated spectral and laboratory datasets to support environmental and agricultural applications. • Communicated technical analysis results in clear visual formats for research teams.

• Master’s Thesis - Modelling soil fertility parameters using Vis–NIR, LIBS and XRF spectroscopy - Leibniz Institute for Agricultural Engineering and Bioeconomy • Acquired and processed spectral data from Vis–NIR, LIBS and XRF sensors for rapid, non-destructive soil characterization. Preprocessing, calibration and quality assessment for multi-instrument datasets. • Developed reproducible Python workflows for the integrated evaluation and visualization of spectroscopic and laboratory data.

Thesis: Geochemical assessment of potentially toxic elements in mine and agricultural soils • Performed total digestion (HF–HClO₄–HNO₃–HCl) and ICP-OES analysis for multi-element quantification. • Conducted five-step sequential extraction (Tessier method) to determine phase-specific metal partitioning and element mobility. • Carried out XRD-based mineralogical characterisation to identify mineral controls on trace-element distribution and release.