The main focus of the faculty’s educational programme was always on the interdisciplinary approach, which provides a systematic and holistic knowledge concerning organisational, economical and engineering problems. The XXI. century’s engineering studies require new challenges in the field of education, it demands the understanding of modern system, control theory, IT, operational analysis, virtual design, management, energy saving and environmental aspects, reliability theory and quality assurance management.
The aim of the faculty’s MSc studies is to deepen the knowledge gained on the BSc studies with mostly theoretical knowledge, but also with practical knowledge that is needed for an engineer graduate. The existing specializations give an opportunity to further develop the insight in certain areas.
Foreign students have the opportunity to attend a full Transportation Engineering Master (MSc), Vehicle Engineering Master (MSc), Logistics Engineering Master (MSc) and Autonomous Vehicle Control Engineer Master (MSc) study in English, which are the best engineering programs in Hungary in all aspects based on Hungarian Government Institution statistics.
Please note that not all specializations start every year based on the interest of the majority of students.
We also offer a full PhD program in the field of transportation, vehicle, logistics engineering.
The information brochure about our educational programmes can be downloaded here!
Requirements of the application are a Bachelor (BSc) degree and an English language certificate. The applicants will have to pass an electronic assessment test and will be invited to a professional interview.
- Applicants of the program shall possess a university degree at Bachelor level preferably in the field of engineering or natural sciences or economics.
- Applicants are acceptable, if they have received their degree with min of 70% results.
- Applicants have to possess a language exam at least in English on B2 level.
- Applicants have to possess a comprehensive knowledge about the chosen topic.
- The applicants are rated based on a scoring system. All applicants are possibly acceptable, who reached at least 60 points of the maximum of 100 points after the application interview.
- Applicants, who reached the minimum threshold, but did not receive a scholarship (e.g Stipendium Hungaricum), are possibly accepted in a self-financing form.
- The amount of self-financing is 3500 Euro/semester (2 semesters per year).
Please note that English language proficiency must be proven by one of the following internationally recognized certificates:
- IELTS min. 5.0
- Cambridge B2 First (FCE) min. 160
- TOEFL iBT min. 72
- Trinity Integrated Skills In English (ISE) min. ISE II
- TOEIC Listening min. 400 / Reading min. 385
- TOEIC Speaking min. 160 / Writing min. 150
- Pearson Academic (PTE) min. 29
- or a Medium of Instruction Certificate.
Details of the scoring can be found here!
Transportation Engineering MSc
The aim of the studies is to train transportation engineers, who will be able to deal with the process planning routine for public transportation and the transportation of goods. They will be able to decide the proper tools for them and deal with issues related to infrastructure, control and IT systems.
Vehicle Engineering MSc
The aim of the studies is to train vehicle engineers, who will be able to maintain and operate road-, railway-, water-, air-, construction-, and material handling vehicles with knowledge gained in the fields of transportation and logistics.
Logistics Engineering MSc
The aim of the studies is to train logistics engineers, who will be able to deal with logistics planning and the systems related to it. They will be able to decide on the proper tools in the field and manage these.
Autonomous Vehicle Control Engineering MSc
The aim of the studies is to train autonomous vehicle control engineers, who will be able to deal with designing, developing and manufacturing autonomous vehicles, simulate networks, test and validate processes and work in a complex environment with various sensor data.