MSc Health and Medical Data Analytics (HMDA)


In contrast to traditional university education in engineering, the M.Sc. in Health and Medical Data Analytics aims to :

  • teach students data analytics for medical applications at 4 top-notch universities in Europe, giving them the chance to specialise in each institution’s key research areas
  • provide students with innovation and business skills in addition to their studies in medical data analytics. We teach students how to convert academic knowledge into a concrete business product or service, e.g. an app that helps patients to cope better with their disease or a database that helps hospitals provide better service to patients. 
  • connect students with MedTech companies and hospitals early on in their studies – through teachers with an industry background, business collaborations in practical projects and a Master’s thesis which is supervised by an academic and non-academic MedTech expert.
  • train students to have an international mindset through a mandatory study abroad phase at one of the programme partner universities.
  • provide practical experiences and equip learners with team skills through innovative teaching, i.e. hands-on, real life projects and internships, in which academic knowledge is put into practice.


The programme is designed for 2 years (120 ECTS): 

  • The first semester comprises core content, focused on data analytics and its technical aspects as well as basic courses in Innovation and Entrepreneurship (I&E). Students acquire competencies in statistical analysis of data, building and assessment of data-based models, data management, and data mining.
  • The second semester focuses on electives at the home university. 

20 ECTS of I&E content are offered during the first year and during the mandatory summer school that brings together students and faculty from the whole consortium. 

  • The third semester is conducted at a partner university depending on the student’s specialisation. 
  • During the fourth semester, students complete the Master’s thesis and an internship with a non-academic partner. 

The universities offer different specialisations:

  • FAU: knowledge acquisition in image processing in computational tomography and magnetic resonance imaging; 
  • UPM: data mining and artificial intelligence techniques;
  • UL: precision medicine with a focus on bioinformatics and biostatistics; 
  • UGA: foundations of medical imaging and bio-health computing. 

Teaching methods focus on team-based, project-oriented learning and exchanging feedback on project ideas and prototypes. Especially in the I&E lab modules, the summer school and the Master’s thesis project, students will develop their own ideas and creative solutions. 


A bachelor’s degree in engineering or related studies and a strong interest in innovation and entrepreneurship are required for admission. 

Graduates in HMDA are computer scientists with excellent skills in information processing, machine learning and data mining. They will develop and use state of the art technology in order to generate, analyse and interpret medical data. By including several lab modules and internships, and with the help of practical courses, students will learn to specifically coordinate their own collaborative projects as well as their studies in general and thus shoulder responsibility – not only for them but also for different working groups. Being educated in medical device regulation / law, students will be prepared to deal with different European healthcare systems and will be an asset to any large MedTech company (e.g. Siemens Healthineers, GE Healthcare, Philips Healthcare) or healthcare start-ups. 

The programme also gives students access to the biggest MedTech network in Europe by connecting them with the community of EIT Health. Being part of the EIT Health network means easy access to support and funding for business ideas through Accelerator and Innovation Projects programs.


Friedrich-Alexander-Universität Erlangen-Nürnberg
Universidad Politécnica de Madrid (Technical University of Madrid) - UPM
Universite Grenoble Alpes
University of Lisbon

Felix Schmutterer
Programme Director