Online admission platform launched by The Technical University in Cluj-Napoca – UTCN is the new platform on which the Technical University of Cluj-Napoca (UTCN) organizes the 2020 admission and offers to the candidates 5011 places for undergraduate education, 2780 places for master’s degree and 195 for doctorate.

Of the 5011 places, 3343 are on budget and 1668 on fee. Of the budget places, 368 are for priority areas, 40 for candidates from rural areas, 12 for graduates from social protection systems and 5 for Roma candidates. For master’s education, the 2780 places are divided in 1920 by budget and 860 by fee.

Among the 1920 budgeted places, 355 are allocated to priority areas. Romanians everywhere have allocated 24 places out of the total for master’s degrees. At the doctorate, candidates will be able to opt for one of the 16 fields to which 195 places are allocated.

The actual registration and classification of candidates will be done on a high-performance platform that allows the registration of all categories of candidates, both in the country and abroad.

The platform was launched on Friday, June 6, and immediately after its launch registered a considerable number of candidates interested in the study programs that the university offers. Candidates can go through a pre-registration stage which is prior to the admission process and which allows them to familiarize themselves with the platform accessed from any desktop device, laptop, tablet, mobile phone, with internet access.
Within the Technical University of Cluj-Napoca, registration is done on commissions. A commission can comprise several faculties, so that, with a single fee, candidates can opt for all fields of study (budget / fee) from all the faculties included in the respective commission.

Admission method, average calculation algorithm, admission criteria and schedule,
as well as the tuition figures can be consulted on the platform, with the particularities related to each of the 12 faculties.

The transition to the online admission process follows a natural, adaptive process, which takes into account the safety of candidates, which takes into account their preferential options and especially, which takes into account relevant classification algorithms for each candidate.




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