Our academic year

The academic year of the Universitat Pompeu Fabra is divided in three trimesters. Each trimester has 10-11 weeks of lectures followed by an exam period of 1-2 weeks. In general, the approximate duration is the following:
First trimester: mid September-December 
Second trimester: January-mid April 
Third trimester: mid April-June 
Presentation of master theses: July
The courses listed below are held during the week (Mon-Fri) exclusively in the afternoon (14h30-20h30).  Activities of the research groups, such as seminars, journal clubs, project meetings, ect. are held througout the day.

Core programme

Mandatory core courses (total 15 ECTS)

All three mandatory courses account for 5 ECTS each. 


Data Science (first trimester, 5 ECTS)

This course introduces fundamental concepts and mathematical tools in data science, with the aim of preparing students for data processing in computational biomedicine. Specifically, the following topics will be covered: 1) Hypothesis testing; 2) Dimensionality reduction, using machine learning algorithms such as manifold learning, unsupervised learning and principal components analysis; 3) Classification, supervised learning and decision making processes; 4) Applications in Big Data, involving methods such as deep learning. See detailed study plan.

Research Methodology (first trimester, 5 ECTS)

This course covers the major considerations and tasks involved in conducting scientific research. It reviews the graduate studies research context, skills and methodologies. It furthermore introduces the essential aspects in research proposal writing and research reporting. See detailed study plan.

Seminars (first, second, third trimester, 2+2+1 ECTS)

Subject of this course are regular organized interactions between the master students and members of their research group. Apart from the supervisor these will be doctoral students, postdoctoral researchers and other senior professors. These interactions include the joined discussion of ongoing scientific projects of different group members as well as the discussion and analysis of scientific articles by others. Master students will make regular presentations on their progress, summarize scientific articles in the reading groups, etc.


Elective courses (total 20 ECTS)

Students can potentially take external elective courses offered by others MSc and BSc degrees of our Departments. Important: Since these courses are from other degrees it cannot be guaranteed that places are available. Furthermore, it cannot be guaranteed that the schedules of these courses are compatible with those of our courses. Availability and schedule compatibility must be checked before enrollment. See full list of external courses.


The following elective courses pertain directly to our master. They are specifically designed to endorse the student with the expertise required to carry out his/her research projects. The academic coordinator of the master and the supervisor of the student’s research project will help the student to select four courses taking the student’s background and interests into account. All courses account for 5 ECTS each. 


Virtual Physiological Human and Digital Twins (first trimester, 5 ECTS)

This subject aims to introduce the students to the digital twin concept applied to the exploitation of the virtual physiological human technologies in healthcare technologies and research. Specifically, it covers: proper classification and modelling of data; integration of real world data and knowledge from experimental models into models and simulations; patient-specific modelling for the mechanistic enhancement of clinical information; verification, calibration and validation of models and regulation of the use thereof.

Advanced Biosignal Analysis (second trimester, 5 ECTS)

Subject of this course is nonlinear analysis of biomedical signals. In the theory sessions we will learn about different advanced signal analysis approaches such as nonlinear predictability measures and Monte Carlo simulations designed for null hypothesis testing. As an example of biomedical signals, we will study why and how the electroencephalogram (EEG) is recorded from inside the brain of epilepsy patients. This will be complemented by the joined discussion of recent scientific literature in the format of journal clubs. In computer laboratory sessions the students will implement the signal analysis algorithms introduced in the theory sessions. Furthermore, students will study in detail EEG recordings provided by our clinical partners. Finally, they will apply their signal analysis algorithms to these recordings and present their results in a session of oral presentations. See detailed study plan.

Computational Cardiology (second trimester, 5 ECTS)

This subject provides a detailed review of the different phases and concepts required for modelling the cardiovascular system in a realistic way. Special emphasis will be given to the generation of 3D patient-specific multi-scale and multi-physic simulations in healthy and pathological conditions, as well as to the in-silico testing of different therapeutic solutions. Additionally, at the beginning of the course there will be an extensive review of cardiac physiology and morphology. Then, the focus will be on the generation of detailed meshes integrating multi-modal data provided by different sources, setting up the geometrical domain where simulations will be run. The remaining lectures will be devoted to the presentation of the state-of-the-art modelling approaches to simulate the most relevant physical phenomena in cardiology: electrophysiology, (electro-)mechanics, and blood flow. See detailed study plan.

Computational Therapies (second trimester, 5 ECTS)

This subject will study the general architecture and implementation aspects of computer-assisted surgery, from planning and simulation to intraoperative navigation and surgical robotics. More specifically the following steps will be investigated: planning of pre-operative trajectories and structures; registration of pre-operative and intra-operative images; tracking of surgical instrumentation; augmented reality; biomechanical deformation models. Lectures will start by introducing the basic theory and existing technological choices. Then, we will analyse and discuss several real computer-assisted systems, also from the point of view of clinical applications. See detailed study plan.

Complexity Science (first trimester, 5 ECTS)

The objective of this course is to introduce the basic methods for the analysis of complex behavior in natural systems. Special emphasis will be made on the processes underlying complexity and collective dynamics in biological systems at all levels, ranging from the behavior of individual cells to populations of organisms and their associated social behavior. At the end of the course, the student will be able to interpret nature in terms of emergence and self-organization. See detailed study plan


Master thesis (25 ECTS)

The master thesis is carried out along the three trimesters. In the first trimester the topic of the master thesis project is defined and planned by the student and his/her supervisor. The time dedicated to the master thesis increases along the three trimesters. Accordingly, the workload of the courses is decreasing along the three trimesters. In particular, as can be seen in the description above, in the third trimester only 1 ECTS from 'Seminars' is taken.