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Description of the title
The Master in Computational Engineering & Industrial Mathematics is an online master’s degree in English, designed to prepare students in the use of advanced tools of computational engineering and mathematics applied to industry. This master’s degree provides solid training in complex systems modeling, algorithm development, data analysis, statistics, optimization, simulation, machine learning and artificial intelligence. Through an applied perspective, students acquire the necessary skills to solve real-world problems in sectors such as logistics, transportation, production, finance, and smart cities, among others. Although the program is online, the final exams are held in person at the UPV Alcoy Campus.
Objectives of the degree
Develop competencies in mathematical modeling and simulation of complex systems.
Training in the design and optimization of algorithms applied to engineering and industry.
Training in advanced data analysis techniques, statistics, machine learning and artificial intelligence.
Apply computational tools to solve real-world problems in sectors such as logistics, transportation, production, finance and smart cities.
To foster skills for data-driven decision making and the implementation of innovative solutions in industrial environments.
Career opportunities
Career opportunities for graduates of the Master in Computational Engineering & Industrial Mathematics include roles in high-demand sectors and positions.
- Data Analyst: Data analysis to improve industrial and business processes.
- Machine Learning Specialist: Development of predictive models and AI systems applied to various sectors, such as production, finance or logistics.
- Quantitative Analyst: Mathematical modeling in finance and insurance, contributing to strategic decision making.
- Industrial Optimization Consultant: Application of algorithms and models to improve efficiency in production processes, logistics, transportation, smart cities, etc.
- Computational Model Developer: Creation and simulation of models in areas such as energy, resource management or smart cities.
- Technological Project Manager in Industry 4.0: Leadership of technological projects in automation and industrial digitalization environments.
- Research: access to doctoral programs and research groups in fields related to the master’s degree.
Aimed primarily at
This master’s degree is designed for graduates seeking to specialize in areas of high demand in the technological and scientific industry.
- Graduates in Computer Science / Computer Engineering, Data Science and Artificial Intelligence.
- Graduates in Mathematics, Statistics, and Industrial Technology Engineering.
- *For graduates in Mathematics, Statistics and Industrial Technology Engineering, the following requirements are also included:
- a) Have passed during the degree a minimum of 12 ECTS between subjects of Programming, Algorithmics, and Computer Science, including a minimum of 6 ECTS of Programming with a general purpose language (e.g., C/C++, Python, Julia, or Java).
- b) Complete the course “Programming for Data Analytics”, which will have 6 ECTS and will be offered by the UPV prior to the start of the master’s degree.
Structure of the master’s degree
Credits: 60 ECTS
Mandatory:30 ects |Electives:18 ects |External internships:0 ects |Final Master’s thesis (TFM):12 ects
Module 1. Compulsory courses :30 ects mandatory
Subject:Computational Engineering
Minimum credits: 12 | Character: Compulsory
Subject:Industrial Mathematics
Minimum credits: 18 | Character: Compulsory
Module 2. Elective courses :18 ects mandatory
Subject:Hot Topics and Applications
Minimum credits: 18 | Character: Elective
Module 3. Master’s Thesis :12 ects mandatory
Subject:Master’s Thesis
Minimum credits: 12 | Subject: Final Degree Project
Internships
The possibility of external internships is not contemplated.
Academic exchange / agreements with other universities
List of higher education institutions with which exchange agreements of interest to the degree are maintained:
- CESKA ZEMEDELSKA UNIVERZITA V PRAZE (Czech Republic)
- VYSOKÁ SKOLA FINANCNÍ A SPRÁVNÍ, O.P.S. (Czech Republic)
- STICHTING HOGESCHOOL VAN UTRECHT (The Netherlands)
- LAB UNIVERSITY OF APPLIED SCIENCES (Finland)
- HAUTE ECOLE `GROUPE ICHEC-ISC SAINT LOUIS-ISFSC` (Belgium)
- HOCHSCHULE AUGSBURG (Germany)
- BUDAPESTI MÛSZAKI ÉS GAZDASAGTUDOMANYI EGYETEM (Hungary)
- Fachhochschule Salzburg GmbH (Austria)
- POLITECNICO DI MILANO (Italy)
- UNIVERSITÀ DEGLI STUDI DI ROMA `LA SAPIENZA` (Italy)
- HÖGSKOLAN I SKÖVDE (Sweden)
Facilities and laboratories
The teaching will be delivered online through live interactive sessions (synchronous teaching) and its recordings can be consulted later through the TEAMS platform.
The teaching methodology will include, among others, the use of the following didactic resources:
- Slides with the main concepts of each topic
- Subject-specific software
- Reference books
- Practical activities to be carried out collaboratively or individually
- Examples of practical exercises solved with the use of software
- Case studies in the industrial or business sector
- Scientific articles
- Discussions in the virtual classroom
- Training videos selected by the teaching team
Master’s Thesis
The master’s thesis focuses on the solution of a real industrial problem using advanced techniques of computational engineering and industrial mathematics. Students will have the opportunity to apply their skills in modeling, optimization, simulation and data analysis to solve a specific problem and develop a practical solution.
The master’s thesis can be carried out in collaboration with a company, institution, or research center, which allows students to work in a real environment and gain practical experience.
In addition, the project can also be an opportunity for students to develop skills in communication and presentation of results and conclusions.
