MScEngineering Management
Italy, Siena
Study location | Italy, Siena, San Niccolò, via Roma, 56 - 53100 - email: l2_gest@diism.unisi.it |
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Academic field | Engineering (JACS H000) |
Type | Master's Degree, full-time |
Nominal duration | 2 years (120 ECTS) |
Study language | English |
Awards | MSc (LM-31 Second cycle degree in Engineering Management) |
Tuition fee | You can estimate the amount to be paid per year at this link |
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Application fee | €40 per program You will receive an e-mail with the payment instructions. |
Entry qualification | Bachelor/Undergraduate diploma (or higher) After you have applied, an Enrolment Committee will assess your competencies and skills against the requirements of the MSc Programme. Admission criteria The competences required to be admitted to the MSc in engineering are: After the evaluation In case of a large number of applications, students who pass the selection based on the submitted documents will also be invited to take part in a remote written test, possibly followed by an interview. The dates of the remote written test will be communicated to the admitted students via email. The entry qualification documents are accepted in the following languages: English / Italian. Often you can get a suitable transcript from your school. If this is not the case, you will need official translations along with verified copies of the original. Procedures at the Italian Diplomatic Representatives Non-EU citizens EU citizens – Non EU citizens with regular permit to stay – Italians with degrees obtained abroad |
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Territory requirements | Applications are accepted from the following territories (based on citizenship): World. |
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Language requirements | English Check the English requirements at the following link admission.unisi.it/?p=1944 |
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Other requirements | A statement of purpose must be added to your application. English Proficiency – B2 level of the Common European Framework of Reference for Languages – CEFR, or higher. |
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More information |
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Overview
The MSc in Engineering Management provides high-level competences for modeling, optimization, decision making and management of organizations. The study programme is focused on industrial economics and marketing, planning of innovation processes and project management. The course also provides fundamentals of mathematical modeling, data and decision analysis and optimization of complex systems.
Objectives
This is a 2-year graduate programme taught entirely in English, attended by both national and international students.
In order to be admitted to this course of studies students must possess background in mathematics, statistics and physics, equivalent to the one achieved in first-level (B.A.) engineering degrees; basics principles of economics, management and programming.
Graduates in Engineering Management are interdisciplinary managers with advanced problem solving skills and a holistic view on modern companies in today’s economic and social context, thus able to develop innovative and sustainable solutions for complex organizations.
Program structure
The MSc in Engineering Management is entirely taught in English.
MIUR degree class: LM-31 Second cycle degree in Management Engineering
Duration in years: 2
Credits: 120
Career opportunities
Graduates in Engineering Management are able to apply knowledge and skills acquired during their studies in all work environments requiring complex decision making processes and analytical skills.
The multidisciplinary approach backed by quantitative methods can be applied to several sectors including production and logistic, financial, consultancy, healthcare or energy sectors among others. Hence graduates in Engineering Management are hired in a wide range of positions by companies and organizations of all sizes.
The skills learned during MSc in Engineering Management can be useful in different positions. Usually, graduates in Engineering Management start in technical positions and may quickly advance to executive and managerial positions. Their typical activities often include the development of quantitative models, optimization algorithms and decision support systems, and the implementation of technological innovations.
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