Description

MSc Engineering Management

The Engineering Management programme offered by the University of Siena 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.

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Duration

2 years

Starting Date

End of September

Tuition Fee

From € 756 to a maximum of € 2,626 per year*

Location

Siena, Italy

*The tuition fee is calculated according to the country of origin and ranges from a minimum of € 756 to a maximum of € 2,626 (per year).

About the programme

Graduates in Engineering Management at the University of Siena 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.

Courses Included

Complex Dynamic Systems
Decision Analysis
Discrete-event Systems
Industrial Economics And Marketing
Innovation Planning And Management
Production Planning And Supply Chain Management
Project And Human Resource Management
System Identification And Data Analysis
Test Of Competence In English – B2

Career Prospects

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.