Students are required to have a Dynamical Systems background in order to proficiently carry out the activities reported in the list below.
If interested, please email the contact professor to verify that the CV is compatible and to obtain further details on the activities.
Innovative control techniques for mechatronic and transportation processes
Duration: 3 months minimum
Contact person: prof. Laura Celentano, This email address is being protected from spambots. You need JavaScript enabled to view it.
Modeling and control of rigid and flexible mechanical and structural systems
Duration: 3 months minimum
Contact person: prof. Laura Celentano, This email address is being protected from spambots. You need JavaScript enabled to view it.
A complex system approach to the study of migration dynamics induced by climate change.
The student needs to have a dynamical systems background and knowledge of Matlab.
Duration: 3 months minimum
Contact person: prof. Pietro De Lellis, This email address is being protected from spambots. You need JavaScript enabled to view it.
Decentralized control of multiagent systems with application to formation control.
The student needs to have a dynamical systems background and knowledge of Matlab.
Duration: 3 months minimum
Contact person: prof. Pietro De Lellis, This email address is being protected from spambots. You need JavaScript enabled to view it.
Development, implementation and testing of different (Deep) Reinforcement Learning algorithms for the Vertical Stabilization of elongated plasma configurations in tokamak devices.
Duration: 2-3 months
Prerequisites: general knowledge of deep-learning techniques, neural networks and RL algorithms; good command of Matlab/Simulink
Contact person: prof. Gianmaria De Tommasi, This email address is being protected from spambots. You need JavaScript enabled to view it.
Development, implementation and testing of (Deep) Reinforcement Learning schemes with applications to the the Vertical Stabilization of elongated plasma configurations in tokamak devices.
The student will be required to work on the integration of in-house Matlab-based simulation tools with control agents developed in Python (+ Keras/TensorFlow)
Duration: 4-5 months
Prerequisites: general knowledge of deep-learning techniques, neural networks and RL algorithms; good command of Matlab/Simulink and Python with Deep-Learning oriented libraries
Contact person: prof. Gianmaria De Tommasi, This email address is being protected from spambots. You need JavaScript enabled to view it.
Modeling, analysis, and control of collective behavior in complex systems and their applications.
The student needs to have a dynamical systems background and knowledge of Matlab.
Duration: 3 months minimum
Contact person: prof. Mario di Bernardo, This email address is being protected from spambots. You need JavaScript enabled to view it.
Nonlinear dynamics and control theory for synthetic biology.
The student needs to have a dynamical systems background and knowledge of Matlab.
Duration: 3 months minimum
Contact person: prof. Mario di Bernardo, This email address is being protected from spambots. You need JavaScript enabled to view it.
Exploiting network opinion dynamics models to predict the emergence of collective behavior in social groups.
The student needs to have a dynamical systems background and knowledge of Matlab.
Duration: 3 months minimum
Contact person: prof. Francesco Lo Iudice, This email address is being protected from spambots. You need JavaScript enabled to view it.
Modeling and distributed control of comoex networks with application to power grids.
The student needs to have a dynamical systems background and knowledge of Matlab.
Duration: 3 months minimum
Contact person: prof. Francesco Lo Iudice, This email address is being protected from spambots. You need JavaScript enabled to view it.