Molecular dynamics simulations and electronic-structure calculations are ubiquitously used in Materials Science, Nanotechnology, and Biophysics. Graduate students in Physics or Chemistry typically have a solid background in statistical mechanics and condensed-matter physics, but often lack knowledge of the numerical algorithms and concepts that are the bedrock for any theoretical work in such areas. The proposed activity aims at filling this cultural gap by providing an introduction to molecular dynamics simulation techniques, quantum mechanical calculations and machine learning methods without previous experience. This makes the activity unique: most available schools on scientific programming are targeted to PhD students/young researchers with a working knowledge of specific methods, while the proposed school is explicitly dedicated to beginners.

The purposes of this School will be:

(i) providing undergraduate students with a basic but detailed overview of the theoretical foundations of classical molecular dynamics and quantum mechanics ab initio methods, as well as combining them using machine-learning interatomic potentials.

(ii) giving an overview of the domains of interesting applications in Materials Science, Nanotechnology, and Biophysics.

(iii) providing the basics for writing and running simple atomistic simulations

At the end of the school the students will have acquired a first-hand experience with numerical simulations for a broad range of common scientific contexts, will be aware of the challenges and open problems in computational physics, and will be able to write their codes for simulating systems of their interest and carry out the pertinent data analysis.

**In the application form please upload your CV and specify clearly your career stage and your motivation in attending the school.**