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ENGINEERING
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Guide for Students
 
Degree Programme Regulation
 
Department
 
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Results of assessment questionnaires (C.P.D.)
 
Level of satisfaction of graduating students (AlmaLaurea)
 
Employment condition (AlmaLaurea)
 
Admission requirements
 
Final exam
 
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Glossary en-it
 
MATHEMATICAL ENGINEERING, Laurea Magistrale (Master of science-level of the Bologna process)
Academic Year 2022/23
DEPARTMENT OF MATHEMATICAL SCIENCES
Collegio di Ingegneria Matematica
Campus: TORINO
Program duration: 2 years
Class LM-44 Degree: MATHEMATICAL MODELLING FOR ENGINEERING
Reference Faculty
BERRONE STEFANO   coord.matematica@polito.it
Program held in Italian, English
 Educational objectives

The objective of the degree program is to train a professional figure who can use engineering technologies and methods of applied mathematics to define and solve complex problems that require detailed mathematical modelling, computer simulations and statistical investigation. Characterised by a strong synergy between mathematics and engineering disciplines, the MSc degree gives students the opportunity to address problems from various enginee... More...

The objective of the degree program is to train a professional figure who can use engineering technologies and methods of applied mathematics to define and solve complex problems that require detailed mathematical modelling, computer simulations and statistical investigation.
Characterised by a strong synergy between mathematics and engineering disciplines, the MSc degree gives students the opportunity to address problems from various engineering fields relating to both artificial systems, constructed or constructible by humans, and natural systems and phenomena.
The programme aims to provide graduates with the skills needed for the following activities:
- Choose the best mathematical model to use, on the basis of a compromise between desired accuracy and tolerated complexity;
- Perform qualitative and quantitative analysis of output generated by the model and of correspondence with the phenomenon to be analysed;
- Perform numerical simulations of natural phenomena, industrial processes and behaviours of materials and structures;
- Perform analyses of statistical data, synthesize them, adapt them to stochastic models of interest in the applications, and utilise them for forecasting purposes in reliability and decisional analyses;
- Apply an engineering "mindset" to problems involving complex systems with a strong interdisciplinary component, using methods available in the various areas of Applied Mathematics.
Students are allowed some freedom in the choice of mathematical methods to study in greater depth and the engineering fields in which to apply them. Individual study plans, which must meet the requirements for training activities and be strongly consistent, are subject to approval by the curricular commission.
The curriculum is intended to ensure all the cognitive tools necessary to practise the profession of mathematical engineer, such as:
- Mathematical modelling, aimed at deducing the most suitable mathematical model to describe applicative problems and analyse their solutions from both a qualitative and a quantitative point of view;
- Numerical simulation, aimed at describing the latest methods of approximation and numerical integration and methods for representing numerical solutions;
- Probability and statistics applied to solving non-deterministic problems and managing and interpreting data stemming from experiments or from probabilistic models;
- Broad engineering skills for application in various sectors.
With the preparation and discussion of the thesis, students have an opportunity to put into practice all that they have acquired, mixing theoretical knowledge and applicative and/or experimental skills as well as providing an original input.

 Career opportunities

The objective of the degree course is to train a professional figure who can use engineering technologies and methods of applied mathematics to define and solve complex problems that require detailed mathematical modelling, computer simulations and statistical investigation.
Characterised by a strong synergy between mathematics and engineering disciplines, the MSc degree gives students the opportunity to address problems from various engi... More...

The objective of the degree course is to train a professional figure who can use engineering technologies and methods of applied mathematics to define and solve complex problems that require detailed mathematical modelling, computer simulations and statistical investigation.
Characterised by a strong synergy between mathematics and engineering disciplines, the MSc degree gives students the opportunity to address problems from various engineering fields relating to both artificial systems, constructed or constructible by humans, and natural systems and phenomena.
The programme aims to provide graduates with the skills needed for the following activities:
- Choosing the best mathematical model to use, on the basis of a compromise between desired accuracy and complexity tolerated;
- Performing qualitative and quantitative analysis of output generated by the model and correspondence with the phenomenon to be analysed;
- Performing numerical simulations of natural phenomena, industrial processes and behaviours of materials and structures;
- Performing analyses of statistical data, synthesize them, adapt them to stochastic models of interest in the applications, and utilise them for forecasting purposes in reliability and decisional analyses;
- Applying an engineering ┐mindset┐ to problems involving complex systems with a strong interdisciplinary component, using methods available in the various areas of applied mathematics.
Students are allowed some freedom in the choice of mathematical methods to study in greater depth and the engineering fields in which to apply them. Individual study plans, which must meet the requirements for training activities and be strongly consistent, are subject to approval by the curricular commission.
The training is intended to ensure all the cognitive tools necessary to practise the profession of mathematical engineer:
- Mathematical modeling, aimed at deducing the most suitable mathematical model to describe applicative problems and analyse their solutions from both a qualitative and a quantitative point of view;
- Numerical simulation, aimed at describing the latest methods of approximation and numerical integration and methods for representing numerical solutions;
- Probability and statistics applied to solving non-deterministic problems and managing and interpreting data stemming from experiments or from probabilistic models;
- Broad engineering skills for application in various sectors.
With preparation and discussion of the thesis, students have an opportunity to put into practice all that they have acquired, mixing theoretical knowledge and applicative and/or experimental skills as well as providing original input.

MSc graduates will have a good basic engineering background and sound mathematical training, enabling them to work as part of design teams to develop mathematical models and simulations, analyse data, perform risk analysis, and solve optimization problems.
Likely employment opportunities for graduates are with manufacturing industries, consulting firms, banks and insurance companies, computer companies, engineering firms specialising in simulation, and research laboratories.

The Study program qualifies the following professional profile/s: Roles and skills:
Mathematical engineer specialised in mathematical modelling and numerical simulation   JOB ROLES:

This is professional figure with both a good engineering and a solid mathematical preparation; especially suitable for work within in research and development and design groups that need in-depth design studies, based on the use of advanced mathematical procedures, to develop mathematical models and simulations.

SKILLS RELATED TO THE ROLE:

- Starting from the application problem, she/he identifies and deduces the mathematical model to use, based on a compromise between desired accuracy and tolerated complexity , searching for a satisfactory consistency with reality and optimizing costs, in terms of time and money.
- She/he uses the latest numerical, visualization and useful solution representation methods to report results to colleagues in other disciplines.

CAREER OPPORTUNITIES:

- Industrial goods manufacturing companies
- IT Companies
- Environmental agencies
- Biomedical industries
- Company that design and/or manage complex civil engineering structures,
- Engineering companies specialized in simulations
- Research centres and laboratories.
 
Mathematical engineer specialized in probability and statistics   JOB ROLES:

This figure can handle company databases and extract information from data on the internet and on social networks.
She/he may take independent initiatives in the planning of experiments or researches, providing original solutions to colleagues in order to get the necessary data.

SKILLS RELATED TO THE ROLE:

- Plans experiments, surveys and market research independently and with a comprehensive view of the company objectives.
- Analyses the research results, identifying and enhancing the information and inferential content and providing a solid foundation to support business decisions.
- Analyses the dynamics of networks (social, biological, infrastructure, logistics).
- Tackles optimization problems by identifying the best solutions to problems - both continuous and discrete, and also on networks - that may also be subject to constraints.
- Using the tools of uncertainty mathematics, tackles problems and situations characterized by high uncertainty, such as those found in the world of insurance, investment, quality, risk analysis, biology and medicine.

CAREER OPPORTUNITIES:

- Statistical companies
- Industrial goods manufacturing companies
- Consulting companies
- Banks
- Insurance companies
- Biomedical and pharmaceutical industries
- Research centres and laboratories.
 
Scientific consultant in industrial service companies   JOB ROLES:

Thanks to interdisciplinary training, the mathematical engineer is particularly suited to work in business organization and IT consultancy firms, where rather than a specific specialization, there is a need for a remarkable cross curricular versatility with generalist skills related to all branches of Engineering, to economic issues and to the forecasting and simulation methods of possible scenarios.

SKILLS RELATED TO THE ROLE:

She/he supports the decision-making processes to improve the production and management, as per commissioned requests occasionally made to consulting firms, thus combining her/his solid training in mathematics and physics with the multiple sector engineering competencies.

CAREER OPPORTUNITIES:

- Industrial goods manufacturing companies
- Consulting companies
- IT Companies
 
Scientific planner   JOB ROLES:

Code and high-tech process planning and production manager.


SKILLS RELATED TO THE ROLE:

- Use the most up-to-date computational methods.
- Collects and analyses relevant data and programs for company purposes.
- Uses numerical and statistical software with expertise, to build computer codes or interfaces from scratch or adapting existing codes to new requirements.

CAREER OPPORTUNITIES:

- Industrial goods manufacturing companies
- IT Companies,
- Engineering companies specialized in simulations
- Research centres and laboratories.
 
   

Qualifications for further studies Knowledge required to continue studies
   

 Expected learning outcomes

After the study of some cross-mathematical disciplines, students can choose between a path directed to the formulation of mathematical models and their numerical simulation and a path directed to the study of random systems, data management, network problems and optimization problems . The elective subjects will still allow an osmosis between the two orientations, thus providing the student with a strong multidisciplinary preparation. The con... More...

After the study of some cross-mathematical disciplines, students can choose between a path directed to the formulation of mathematical models and their numerical simulation and a path directed to the study of random systems, data management, network problems and optimization problems .
The elective subjects will still allow an osmosis between the two orientations, thus providing the student with a strong multidisciplinary preparation.
The conclusion of the curriculum includes the writing of a thesis related to an assignment completed independently by the student, that highlights either the innovative use of mathematical methods known for the specific application or the development of innovative mathematical methods.
The subjects contained in the study program are divided in learning areas and defined by the "Dublin descriptors" shown in the chart on panel A4b - expected learning outcomes.



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