Graduate School of Economics and Political Science
- Direction
- Prof. Margarita Torre Fernández, Prof. Iñaki Úcar Marqués
- Language
- English
- Attendance
- On-campus
- Credits
- 60 ECTS
- Campus
- Madrid - Puerta de Toledo
- Applications
-
CLOSED
☛ Places available: 40
- Departments
- Juan Linz Institute (IJL), UC3M-Santander Big Data Institute (IBiDat), Social Sciences Department, Statistics Department, Computer Science and Engineering Department
CONTACT
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APPLICATION FOR ADMISSION
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- Inicio
Digital technology has revolutionized society and the way we study it. Much of human interaction is recorded in the form of a digital footprint, and analyzing it allows us to gain an unprecedented understanding of society and how it works. In this new context, the figure of the computational social scientist emerges. This new profile combines the characteristics of the social scientist with new computational approaches based on predictive modeling, text analysis and network science to analyze society in a new and revealing way.
The Master in Computational Social Science offers specialized training in cutting-edge computational and quantitative analysis techniques oriented to the study of the Social Sciences. This program prepares you to take advantage of complex data and advanced computational tools to understand society and human behavior.
The Master is preferably geared towards students with a background in Social Sciences, Economics, Communication and Law, and prepares them to work in the professional and academic fields, and to lead and supervise interdisciplinary teams in the field of Computational Social Sciences.
│MASTER IN NUMBERS
- ☛ Maximum 35 students per class
- ☛ 90% of professors with Ph.D. degree
- ☛ The demand for computational social scientists has grown quickly in recent years and is expected to grow even more in the future.
- CURRICULUM
- CURRICULUM
📥 │ Subject topics
Formative Complements * Subjects ECTS TYPE Language Introduction to R programming 3 FC 
Basic statistics 3 FC Year 1 - Semester 1
Year 1 - Semester 2
General subjects Subjects ECTS TYPE Language Social and ethical issues of Big Data & AI 3 C Survey research methodology II 3 C Social network analysis 3 C Master's Thesis Seminar 3 C Data harvesting 3 C Text mining 3 C Advanced modelling 3 C Causal inference for Social Science 3 C Master's Thesis Subjects ECTS TYPE Language Master's Thesis 6 C vacio * Formative Complements: all students must take these courses/complements. Provided a student have a sufficient level on these subjects based on his or her previous degree or complementary training, the Master´s Coordinator will decide on the possibility of him or her skipping these courses/ complements. Check the requirements for access to the master's degree.
C) Compulsory: 54 ECTS
Master's Thesis: 6 ECTS
course Programs
- QUALITY
GENERAL COURSE INFORMATION
☛ First year offered: 2022
PROGRAMME’S QUALITY ASSURANCE
The Academic Committee of the Master’s programme complies with the SGIC-UC3M and it is responsible for the follow-up, analysis, review, assessment and quality of the program, it contributes with proposals to improve the program and produces the “Memoria Académica de Titulación” (Programme Report).
FACULTY AND COURSE PLAN
- CURRICULUM
- FACULTY
Detailed information about the Master's faculty
UC3M FACULTY
- BENÍTEZ, SANDRA
Department of Statistics
Assistant Professor
PhD
Brief CV
- CALLEJO, PATRICIA
Telematic Engineering Department
Assistant Professor
PhD
- GUERRERO, VANESA
Department of Statistics
Associate Professor
PhD
Brief CV
- KOLIC, BLAS
UC3M-Santander Big Data Institute
Postdoctoral Researcher
PhD
Brief CV
- LAHDELMA, ILONA
Department of Social Sciences
Postdoctoral Researcher
PhD
Brief CV
- MORALA, PABLO
Department of Statistics
Assistant Professor
PhD
- SÁNCHEZ, ANXO
Department of Mathematics, GISC
Full Professor of Applied Mathematics
PhD
Brief CV
- TORRE FERNÁNDEZ, MARGARITA
Department of Social Sciences
Associate Professor
PhD
Brief CV
- ÚCAR, IÑAKI
Department of Statistics
Distinguished Researcher
PhD
Brief CV
- VILLAMIL, FRANCISCO
Department of Social Sciences
Ramón y Cajal Fellow
PhD
Brief CV
EXTERNAL FACULTY
- ÁLVAREZ LIÉBANA, JAVIER
Assistant Professor
PhD
UNIVERSIDAD COMPLUTENSE DE MADRID
- IRAZABAL, ELEN
Artificial Intelligence Specialist
Graduate in Law
ADVOCATUSAI
- NOGUERA FERRER, JOSÉ ANTONIO
Department of Sociology
Associate Professor
Director of the Analytical Sociology Group
PhD
UNIVERSITAT AUTÒNOMA DE BARCELONA
- NOVAES, MARCO
Senior Data Scientist
Master
BAIN & COMPANY
- PÉREZ HERNÁNDEZ, EMMA
Research Data Analyst
Master in Economic Development and Growth
Master in Computational Social Sciences
FEVER
- SALAZAR, LEIRE
Senior Researcher
PhD
INSTITUTE FOR PUBLIC GOODS AND POLICIES (IPP)
CSIC
- TORRIJOS CARUDA, CARMEN
Expert in Artificial Intelligence, Digital Transformation and Technology Integration
Master
PRODIGIOSO VOLCÁN
- BENÍTEZ, SANDRA
- ADMISSION
- SCHOLARSHIPS
UC3M TUITION GRANTS FOR ACADEMIC YEAR 2026/2027
CALL FOR APPLICATIONS AM01-26/27* │ CLOSED
A maximum of 3 grants have been announced for the academic year 2026-2027 to cover the net tuition fees for students admitted to the Master's program, with the following provisions:
- 3 grants of €1,500
To apply for the grant, you must have formalized the application for admission to the Master's Degree.
Application deadline: 31 May 2026
Partial decisions:
- First decision published on 12 March 2026
- Second decision published on 4 June 2026
- third and final decision: from 22 June 2026 (applications submitted from 1 April to 31 May 2026)
* The number of grants and their amounts specified in the call for applications may vary depending on the conditions of the candidates applying for them, and may even remain unawarded based on the assessment of the Selection Committee for each program
_______
General information on scholarships
For more information on specific scholarships of interest, awarded by the Universidad Carlos III de Madrid as well as other agencies or organizations, please refer here:
- PRACTICAL INFORMATION
MASTER’S COURSE SCHEDULE
_______
FORMATIVE COMPLEMENTS
📌 Formative Complements for the 2026/27 academic year will be taught ON-CAMPUS and the dates and schedules are as follows:
- Introduction to R Programming:
- 31 August | 10:00-14:00h
- 2 and 4 September | 16:00-20:00 h (two 2-hour slots)
- Basic Statistics: 1, 3 and 7 September | 16:00-20:00 h (two 2-hour slots)
The exams will be held on 8 September at 15:00 h (Introduction to R Programming) and 16:30 h (Basic Statistics).
- Introduction to R Programming: