Intern - Computational Chemistry

Step into a career with ASM, where cutting edge technology meets collaborative culture. ​

For over 55 years ASM has been ahead of what’s next, at the forefront of innovation and what’s technologically possible. With more than 4,500 ASMers representing 70 nationalities, our people and our advanced semiconductor devices are playing a crucial role in trends such as 5G, cloud computing, AI, and autonomous driving.  But we’re more than just a tech company. We value diversity, inclusion and sustainability as we strive to make a positive impact on the world.  Our development programs help support your growth, shaping your future and pushing the boundaries of innovation to unleash potential.  

Internship Opportunity: Computational Chemistry Intern (Leuven, Belgium) Summer 2026

About the Internship

We are offering an internship opportunity for students or early-career researchers interested in computational chemistry, data science, and AI-driven materials discovery. This internship focuses on building structure–property relationships for smart precursor discovery, laying the foundation for future AI projects in advanced materials research.

Key Learning Objectives:

• Build and curate a machine-readable chemical library.


• Understand key molecular descriptors and their influence on physical/chemical properties.


• Gain experience in computational chemistry 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 create molecular structures and 3D geometries using online databases


• Collect and organize literature data for relevant physical and chemical properties


• Data pre-processing and feature engineering/extraction


• Perform descriptor calculations and analyze correlations with target properties


• Run DFT calculations on select molecules


• Develop and refine predictive models for property estimation


• Document workflows and contribute to internal knowledge base for AI projects

Preferred Qualifications:

• Master’s student or PhD candidate in Chemical Engineering, Chemistry or related fields (Mechanical Engineering, Materials Science, Applied Physics, or Mathematics with strong chemistry interest).


• Experience with DFT simulations.


• Interest in machine learning and artificial intelligence


• Hands-on experience with Python and Jupyter notebooks.


• Understanding of Python ML scientific libraries and toolkits


• Strong analytical skills and interest in computational chemistry and data driven applications.

What You’ll Gain:

• Hands-on experience in computational chemistry and data-driven modeling.


• Practical skills in Python-based data analysis and AI preparation workflows.


• Insight into structure–property relationships and their role in materials discovery.


• Exposure to industry-relevant research and innovation in semiconductor materials.


• Close collaboration with ASM corporate R&D and Chemistry Innovation teams.