We cordially announce the first Ph.D.-level course organized during the SimEA project:


Course Title: Computational Approaches for Complex Molecular Systems

Level: Ph.D., ECTS: 5, Lectures/week: 2 (75 min. each)

Instructor’s Name: Vangelis Harmandaris

Course Purpose and Objectives

The students will become familiar with fundamental techniques of molecular, primarily classical simulations (Monte Carlo and Molecular Dynamics), which are used to understand and predict properties of microscopic systems in materials science, physics, biology, and chemistry. This is an interdisciplinary course for students from diverse backgrounds, such as physical sciences, applied mathematics, and engineering.  All students will obtain experience in multi-scale modelling, as well as on synergistic approaches between simulations and data analytics methods. A simulation project composed of scientific research, algorithm development, and presentation is required.

Learning Outcomes

By the end of the course, students will acquire knowledge of state-of-the-art mathematical and computational methodologies and algorithms across diverse fields that will allow them to:

  • Have a good understanding of multi-scale simulations and data analytics approaches for studying complex molecular systems;
  • Have experience in applying simulation methods and algorithms for solving problems in physical sciences and engineering;
  • Be able to use, and modify, open-source simulation packages for studying complex systems with realistic models;
  • Acquire experience in using large-scale computational infrastructures in order to deal with high dimensional systems;
  • Be able to work independently on projects, and develop skills in designing and delivering research seminars;
  • Enhance their understanding of synergistic simulation/data analytics methodologies;
  • Critically assess and evaluate molecular models and results from multi-scale simulations against existing data in the literature.