MSE Master of Science in Engineering

The Swiss engineering master's degree


Ogni modulo equivale a 3 crediti ECTS. È possibile scegliere un totale di 10 moduli/30 ECTS nelle seguenti categorie: 

  • 12-15 crediti ECTS in moduli tecnico-scientifici (TSM)
    I moduli TSM trasmettono competenze tecniche specifiche del profilo e si integrano ai moduli di approfondimento decentralizzati.
  • 9-12 crediti ECTS in basi teoriche ampliate (FTP)
    I moduli FTP trattano principalmente basi teoriche come la matematica, la fisica, la teoria dell’informazione, la chimica ecc. I moduli ampliano la competenza scientifica dello studente e contribuiscono a creare un importante sinergia tra i concetti astratti e l’applicazione fondamentale per l’innovazione 
  • 6-9 crediti ECTS in moduli di contesto (CM)
    I moduli CM trasmettono competenze supplementari in settori quali gestione delle tecnologie, economia aziendale, comunicazione, gestione dei progetti, diritto dei brevetti, diritto contrattuale ecc.

La descrizione del modulo (scarica il pdf)riporta le informazioni linguistiche per ogni modulo, suddivise nelle seguenti categorie:

  • Insegnamento
  • Documentazione
  • Esame

Modules: 19

Advanced Project Management (CM_AdvProjMgmt)

The goals of an organization can be efficiently pursued only through proper project management, as a mean able to consistently tackle their needs. Thus the role of the Project Manager become essential, as responsible to achieve the objectives, respecting the constraints determined by the project context. Modern Project Managers must have in-depth technical and management knowledge.
The course provides the students…

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Management of Complex Processes (CM_ComplPro)

One of the biggest challenges encountered in management is recognizing opportunities and making use of them while giving consideration to the associated risks. The constantly increasing dynamism and complexity of the environment in which companies and organizations operate is, however, making it difficult to take successful decisions. Multifactorial correlations, non-linearities, feedback effects and time lags make…

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Innovation and Changemanagement (CM_InnChang)

The module aims to explain the operational planning and management of innovations to students on the basis of an integrated innovation management model, as well as introducing them to the relevant concepts. This will enable students to establish links to various company-internal and company-external interfaces as part of innovation projects and to correctly interpret and influence these. In this module, students will…

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Innovation and Lean (CM_InnoLEAN)

The course introduces the concepts of Lean innovation and lean thinking. It also foster a complex serious-gaming session where the students can develop their own factory and implement its innovation path. Indeed, the student will be able to devise and implement a production practice that considers to be waste the expenditure of resources for any goal other than the creation of value for the customer.

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Integrated Sustainable Management of Production Systems (CM_IntSust)

Companies are increasingly interested in conducting their activities so that a long-term future is assured for its business, society and environment. The purpose of this class is to deal with the well-recognized but sometimes vague concept of sustainability from an engineering perspective. The module is meant to introduce students to the implementation of sustainable management in industries and provide them with…

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Quality and Risk Management (CM_QRM)

The CM_QRM addresses the most relevant basics in integrated quality and risk management. Theory is applied and specified by examples and case studies. The Module concentrates on current standards and best practices on quality and risk management and introduces the most established approaches.

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Applied Statistics and Data Analysis (FTP_AppStat)

Students are introduced to statistical tools used in the industrial sector, and particularly in process and quality control. In this module, students learn to plan and conduct statistical evaluations independently.

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Digital Image Processing (FTP_DigImPro)

The goal of this module is to teach the fundamentals of image processing, while putting emphasis on their mathematical and algorithmic principles. In addition, specific 2D and 3D industrial and biomedical applications will be treated.

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Modelling Simulation and Optimisation (FTP_ModSim)

Modelling, simulation and optimization are fundamental to solving problems in a number of fields of science, technology and life. Students will learn to design, implement, simulate, and optimize a model of dynamic system. Simulation, the exploration of the dynamic behavior of the model in time and space, is discussed for both continuous and discrete-event systems. Simulating a model allows the evaluation of…

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Multi-agent systems (FTP_MultiASys)

Natural, social, and engineered complex systems can be modelled as being composed of agents interacting with one another and their environment. This course introduces students to the theory, tools and techniques for understanding and solving problems related to such systems. 

The course is composed of two parts. In the first one, both cooperative…

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Multiphysics (FTP_Multiphy)

The module gives students insight into the modeling and simulation of coupled effects (multiphysics). The module provides an overview on the different application fields of multiphysics modeling and simulation in industry. Students learn the methodical procedures that are necessary for successfully solving modeling and simulation problems in the different areas of engineering and physics. The consolidation and…

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Optimization (FTP_Optimiz)

This course offers an introduction to optimization, emphasizing basic methodologies and underlying mathematical structures. Optimization refers to the application of mathematical models and algorithms to decision making.  A large number of quantitative real-world problems can be formulated and solved in this general framework. Applications of optimization comprise, for instance, decision problems in production…

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Ordinary Differential Equations and Dynamical Systems (FTP_OrdDiff)

In this module, students learn which class of dynamical phenomena can be described with systems of ordinary differential equations. They learn to recognize the fundamental behavior patterns of these systems and also to develop simulation models for them.

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Advanced robotics (TSM_AdvRobot)

In this module, basic and advanced robotics knowhow is developed necessary for leading-edge, innovative industrial and service applications with robot manipulators.

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Autonomous mobile robot systems (TSM_AutMobRoS)

Mobile robots are complex mechatronic systems often interacting autonomously with their environment. The course combines theoretical foundations for coordinate transformations, sensor fusion, planning and control with examples in ROS. Tests of these complex systems can be conducted in simulated environments to speed up development and minimize risk of damage. Data from live tests can be recorded for later reuse and…

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Automatic Drive Systems (TSM_AutoSys)

This module treats methods of concept, dimensioning and development in the servo drive technology sector which are particularly compatible with the various industries.

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Industrial Control (TSM_IndContr)

The Machine and Production Operations Control is the core of the module, with focus in PLC and CNC applied to manufacturing and practical laboratory and industrial experiences in logic and numerical control for manufacturing.

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Integrated Automation (TSM_IntAuto)

In an automation system in manufacturing technology or process automation, sensors measure non-electric values and actuators, such as drives, influence the process. The individual components are controlled by control systems and automatic controllers, connected with industrial networks, and supervised by humans.

The emphasis of this module is on the selection and determination of the individual components, bearing in…

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Model predictive control (TSM_PredContr)

Model Predictive Control (MPC) is an optimisation-based approach to control systems and processes. The general mathematical formulation of MPC allows it to be applied to a broad range of systems and considers system constraints intrinsically. The advances in optimisation methods and available computational power have made MPC a valuable alternative to classical control approaches also for fast dynamic systems. Today,…

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