Objectives and competences

Technological advances and the digitization of the healthcare environment have led to an increase in the volume of data in recent years, from a wide variety of sources such as sensors, medical devices, clinical records and wearables.

This wealth of massive data in the field of health care requires professionals capable of extracting information that can be applied to improve the clinical care of patients and health care users. Data Science is one of the disciplines that responds to this demand, which, according to some, is growing by more than 50% every year. This percentage is even higher in the case of data scientists specializing in health.

Basic information

TypeMaster's degree
Faculty or schoolFaculty of Mathematics and Computer Science
Branch of knowledge
  • Interdisciplinary
Mode of delivery
  • On line
Credits120
Length of course2 academic years
CoordinationPETIA IVANOVA RADEVA
Open pre-enrolmentNo
Open enrolmentNo
Lead to doctoral studiesYes
Admission for applicants not holding a degree qualificationNo
Main university information Master's degree course homepage
InteruniversityYes
Main universityUniversitat Rovira i Virgili
Universities
  • Universitat Rovira i Virgili
  • Universitat Politècnica de Catalunya
  • Universitat Barcelona
  • Universitat Autònoma de Barcelona
  • Universitat Lleida
  • Universitat Girona
  • Universitat Vic - Universitat Central de Catalunya
  • Université Grenoble Alpes
Bridging coursesNo

Objectives and competences

Objectives

The official international Master's Degree in Health Data Science (MHEDAS) is designed to meet this expected demand and has the following main objectives:

  • To train data scientists to manage and analyse large volumes of health data, and to provide solutions with an impact on the improvement of health care.

  • To provide the interdisciplinary training necessary to identify and valorise the opportunities of data science applied to health challenges.

  • To train entrepreneurs in the field of digital health in Europe who can create the necessary tools to manage, analyse and extract information from big data in the clinical environment and identify business opportunities.

Competences

Access and admission

Applicant profile and access requirements

Recommended applicant profile

Access requirements and conditions

General requirements
In accordance with Article 16 of Royal Decree 1393/2007, of 29 October, students wishing to be admitted to a university master's degree must hold one of the following qualifications:

  • Official Spanish university degree.

  • A degree issued by a higher education institution within the European Higher Education Area framework that authorizes the holder to access university master's degree courses in the country of issue.

  • A qualification issued by an institution outside the framework of the European Higher Education Area. In this case, applicants must request homologation of the degree to its equivalent official Spanish university qualification or obtain express approval from the University of Barcelona, which will conduct a study of equivalence to ensure that the degree is of a comparable level to an official Spanish university qualification and that it grants access to university master's degree study in the country of issue. Admission shall not, in any case, imply that prior qualifications have been recognized as equivalent to a Spanish master's degree and does not confer recognition for any purposes other than that of admission to the master's degree course.

Pre-enrolment

Calendar

Required documentation

Selection criteria

Notification

Enrolment

As a general rule, at the UB you will be required to enrol online. Remember that you can lose your place if you do not enrol on the day you have been assigned

Course curriculum

Subjects and course plans

Distribution of credits

Type ECTS
Compulsory 67.5
Optional 28.5
Compulsory placements 15
Compulsory final project 9
TOTAL 120

List of subjects

Subject Type Language Credits
Specialization: Health Data Science
Activities with Public and Patients Compulsory 3
Advanced Health Data Analysis Compulsory 6
Advanced Medical Image Analysis Optional 4.5
Biomedical Data Challenges Optional 3
Biomedical Sensors and Signal Processing Optional 3
Biomedical Statistics Compulsory 6
Biomedicine for Engineers Optional 4.5
Business Lab Compulsory 6
Clinical Omics and Translational Medicine Optional 4.5
Complex Networks Optional 4.5
Computational Epidemiology Optional 4.5
Computer-Aided Diagnosis and Decision Making Optional 4.5
Deep Learning Compulsory 6
Electronic Health Records Compulsory 4.5
Environmental Health Data Analysis Optional 3
Ethics, Regulation and Privacy Compulsory 4.5
Final Project Compulsory 9
Health Data Integration Optional 3
Health Data Visualization and Communication Optional 4.5
High-Performance and Distributed Computing Compulsory 6
In-Company Placement Compulsory 15
IoT and AI for Health Optional 3
Machine Learning Compulsory 6
Medical Imaging Compulsory 4.5
Prediction of Dynamic Behaviour in Molecular Networks Optional 3
Project and Research Methodologies Compulsory 4.5
Proteomics for Health Research Optional 3
Scientific Programming Compulsory 4.5
Summer School Compulsory 6
Text Mining for Healthcare Optional 3
Tools for Neuroengineering and Neuroimaging Optional 3

Previous years

Placements

Career opportunities

What can you work on ?

  • Entrepreneur in the field of digital health
  • Data scientist in pharmaceutical companies or the bio sector
  • Data-driven project manager
  • Biomedical data scientist in research centres/groups or in hospitals
  • Head of medical informatics in a hospital
  • Advisor on data analysis in health research institutes
  • Advisor for public organisations on public health management

Contact us

sec.mat.inf@ub.edu

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