Advancing predictive analytics, which aims to answer the questions "What will happen?" and "Why will it happen?", prescriptive analytics focuses on transforming prediction insights into actionable recommendations to answer the questions "What should be done?" and "Why should it be done?". The core of prescriptive analytics involves different concepts, ranging from interpretable prediction models to optimization approaches to suggest the best actions based on a prediction and illustrate each action's implications into the predicted outcome.

In this project, the candidate will work to develop new visual analytics and visualization solutions that support the investigation and understanding of a prediction and allow for the representation of multiple actionable choices and their implications. The candidate will work on cutting-edge topics such as model interpretability and explainability, explainable machine learning visualization, intelligent agents, and predictive visual analytics, helping to reduce existing barriers and increase trust in the analytical process.

The candidate is expected to author high-quality scientific papers and showcase the outputs of this work at international conferences. The position will be with the Visualization cluster of the TU Eindhoven under the supervision of Dr. Fernando Paulovich. Opportunities for externships with international collaborators are also possible.

The visualization cluster (https://research.tue.nl/en/organisations/visualization) at TU/e has a strong track record in visualization and visual analytics for ML models and high-dimensional data. It has generated several award-winning contributions at major visualization conferences (IEEE VIS, IEEE InfoVis, IEEE VAST, EuroVis); several successful start-up companies (MagnaView, Process Gold, and SynerScope); and several techniques that are used on a large scale worldwide.