Leuven, Belgium
Internship Explorer
Internship Explorer
We are offering an internship opportunity for students or early-career researchers interested in computational materials science, data analytics, and AI-driven discovery. This internship focuses on building structure–property relationships for accelerated materials discovery, preparing datasets and workflows for future AI projects in advanced semiconductor research. Key Learning Objectives: - Learn how to build and curate a machine-readable materials library. - Understand key descriptors and their influence on electronic and physical properties. - Gain experience in computational materials science workflows and data-driven modeling. - Apply Python-based data analysis and modeling techniques (Jupyter notebooks). - Explore the integration of computational chemistry tools with data driven property prediction. Key Responsibilities: - Import or build bulk structures for ALD-relevant systems using online resources and internal specifications - Collect and organize literature data for electronic and physical properties - Data pre-processing and feature engineering/extraction - Perform descriptor calculations and analyze correlations with target properties - Perform DFT calculations to complement information from databases - Develop and refine predictive models for property estimation - Document workflows and contribute to internal knowledge base for AI projects
