Dottorato in Ingegneria

EnerChem is a high-level educational initiative aimed at graduate students, PhD candidates, and early-career researchers working in the field of chemistry for energy.

The formulation of the damper design problem as a multi-objective optimization problem involving three competing objectives: minimization of interstory drift, floor acceleration, and axial forces in the supporting columns.

The call for applications provides Erasmus+ study and internship mobility grants for students enrolled in a third-cycle course (PhD, Specialization School) at the University of Messina to travel to some of the partner universities.

This talk introduces PhD scholars to the principles of Design Thinking—empathizing with real users, reframing problems, ideating creatively, and iteratively prototyping solutions and demonstrates how these tools can strengthen the research process.

The  module  aims  to  develop  an  understanding  of  stochastic  modelling  and  its application to the analysis of structures subjected to random loads. Stochastic models  of  natural  actions  (e.g.  earthquake  ground  motion)  will  be  explored.

This talk introduces some neural network architectures that leverage convolution operations, starting by reviewing one-dimensional (1D) convolutions in the context of machine learning and discussing essential implementation aspects.