Candidates interested in applying to Master’s Degree Programme in Autonomous Vehicle Engineering (MOVE) for the academic year 2024-25 are warmly invited to upload their applications by directly accessing “Universitaly” website at www.universitaly.it.
Usually, the procedures for the incoming academic year start on March-April. After the application through Universitaly website, candidates to MOVE Program will receive the reply to proceed with the VISA application at their local Embassy.
To speed up the admission process and receive the admission letter to be uploaded during the application through Universitaly website, candidates could ask the preliminary verification of admission requirements by using the following form (click here).
To proceed with the filling of the google form, accessible by a personal Gmail account, candidates are invited to prepare the following documents to be uploaded, separately, in .pdf format:
- Copy of Passport
- Bachelor Certificate
- Transcript of Records that includes CGPA
- English Language Certification or Medium of Instruction (MOI)
- Statement of Purpose
- Letters of Recommendations
Surface, air and marine transport is today in a phase of profound transformation in order to include elements of greater autonomy. These elements of autonomy range from simple forms of enhanced control of a single vehicle to the complete execution of the mission, also in coordination with others, without any intervention by the human pilot. The design of autonomous vehicles requires knowledge in different cultural areas, namely: modern industrial engineering and recent advances in information & communication technology. The Master of Science (Laurea Magistrale) in Autonomous Vehicle Engineering (LM MOVE) aims to train engineers with intercultural skills, who master themes such as:
- Design and management of autonomous land, air and seatransport systems
- Fusion of information to make decisions in real time
- Sensors and algorithms for driving, navigation and control with high autonomy level
- Integration of the autonomous vehicle in complex environments.