Outgoing students
General information
Students can participate in three different Erasmus programs:
- Erasmus+ Study
- Erasmus+ Traineeship
- Erasmus Extra EU
To participate in the Erasmus Traineeship and Erasmus Extra EU programs, you have to identify the place where you would like to spend a period for the traineeship of at least two months in collaboration with a Professor of DISCo who works on an area of your interest and who can propose you the place (University/Company) where you can spend your Erasmus period.
Notes:
- For Erasmus+ Study (to attend classes and take exams) there is only one selection period during the year, usually in January.
- For Erasmus+ Traineeship there are two selection periods during the year, usually in February and July.
- For Erasmus Extra EU there are two selection periods during the year, usually in February and July.
Detailed information about the Erasmus programs and the calls for applications are available at the University portal.
Destinations for the current Accademic Year may be found in the document titled Destinations.
Presentation of the international mobility opportunities 2024-2025
Presentation of the international mobility opportunities 2023-2024
- ESSCA (Anger) - Waste Reduction Using Deep Reinforcement Learning for Perishable Inventory Systems with Two Demand Classes. The student must formulate the problem as Markov decision process. He/she will apply the Deep Reinforcement Learning algorithms to determine the optimal age and the optimal discount level that maximize the total profit. (ask to: fabio.stella@unimib.it)
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ESSCA (Anger) - Performance of Q-reinforcement learning with reward shaping functions for perishable inventory systems. The student will formulate the problem as Markov decision process. He/she will apply the reward shaping technique and compare the results with the literature of perishable inventory systems. (ask to: fabio.stella@unimib.it) -
KU Leuven - Co-clustering methods and individual specific networks. The goal is to study, develop and apply machine learning algorithms, with specific reference to bi-clustering, to analyze gene expression data for precision medicine when the modeling paradigm is represented by individual specific networks. (ask to: fabio.stella@unimib.it) -
University of Oslo - Managing technical and architectural debt, Architectural smell prioritization, Migration to microservice architectures. (ask to: francesca.arcelli@unimib.it) -
University of Poznan - Code representation and analysis using ML, code maintenance and evolution, incl. metrics, techniques and predictions. (ask to: francesca.arcelli@unimib.it) -
TU Wien - Quality control (testing and checking) of Cyber-physical Systems developed with Simulink (ask to: leonardo.mariani@unimib.it) -
TU Wien - Design of Sustainable AI-based Services for edge/IoT computing. (ask to: leonardo.mariani@unimib.it)