AI-Driven Computational Chemistry Intern (Summer 2026)

Dormont Manufacturing Co

Vlaams-Brabant

Sur place

EUR 20 000 - 30 000

Plein temps

14 jours+

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Résumé du poste

Dormont Manufacturing Co is offering an exciting internship opportunity as a Computational Chemistry Intern in Leuven, Belgium for Summer 2026. This internship focuses on computational chemistry and data-driven materials discovery, allowing you to work on building structure-property relationships vital for future AI projects. Ideal candidates are Master’s or PhD students with experience in Python and a strong interest in computational chemistry.

You will gain hands-on experience in advanced modeling, collaboration with ASM's R&D teams, and contribute to innovative projects in semiconductor materials.

Qualifications

  • Students or early-career researchers in Computational Chemistry or related fields.
  • Experience with DFT simulations preferred.
  • Strong analytical skills and interest in data-driven applications.

Responsabilités

  • Import or create molecular structures and 3D geometries using databases.
  • Collect and organize literature data for properties.
  • Run DFT calculations on select molecules.
  • Develop and refine predictive models for property estimation.

Connaissances

Computational chemistry
Data science
Python
Machine learning
DFT simulations

Formation

Master’s student or PhD candidate in relevant fields

Outils

Jupyter notebooks

Description du poste

Dormont Manufacturing Co is offering an exciting internship opportunity as a Computational Chemistry Intern in Leuven, Belgium for Summer 2026. This internship focuses on computational chemistry and data-driven materials discovery, allowing you to work on building structure-property relationships vital for future AI projects. Ideal candidates are Master’s or PhD students with experience in Python and a strong interest in computational chemistry.

You will gain hands-on experience in advanced modeling, collaboration with ASM's R&D teams, and contribute to innovative projects in semiconductor materials.

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