Supervisor: Full Professor Carlo Nervi 

Abstract: 

This project aims to predict periodic molecular structures of High Energy Materials and/or Pharmaceutical Drugs using the USPEX code. The two target areas share common methodological goals: to identify potential polymorphs and co-crystals that could lead to enhanced or tailored material properties. The project will compare the feasibility and accuracy of different computational approaches, including Machine Learning (ML) and Molecular Mechanics (MM), against Density Functional Theory (DFT) benchmarks. Publication in journal is possible, if enough degree of innovation is obtained.

Internship duration: minimum 2 months

Internship start date: no earlier than April 1, 2026

Requirements for the candidate:

— basic knowledge of quantum mechanics and material science;

— basic knowledge of crystallography and USPEX are welcomed, but not mandatory;

— basic knowledge of unix and scripts;

— open mind flexibility, enthusiasm.

Monthly compensation: not available. High-impact results and strong engagement may open the opportunity to continue with the research group after the internship.

Contact person: Carlo Nervi, C.Nervi@skoltech.ru