I worked as a data scientist in the Turbine Data Team. My tasks included:* Development of statistical methods to improve the evaluation of in-vitro and in-silico experimental and simulation results.* Implementation of statistical learning algorithms in R and Python, involving:- k-means clustering- principal component analysis- logistic regression* Data visualization using R's ggplot and Plotly

Experimental work involving label-free biosensors to observe and quantify single human cell adhesion in real-time. As a student researcher, my work included the planning of the experiments, executing them in a state of the art biological laboratory, and the evaluation of the results using commercial softwares, like Matlab and Origin Pro. In my BSc thesis I have developed a way to quantify the real-time perturbative effect of surface receptor-specific ligand molecules in single HeLa and BJAB cell-lines using a high-spatial resolution, optical, label-free biosensor. The quantitative relationship between the concentration of the compound and the parameters of the sigmoidal function characterizing the cell adhesion was established.