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Master in Machine Learning and Health

Graduate School of Engineering and Basic Sciences

Escuela de Ingeniería y Ciencias Básicas
Direction
Prof. Vanessa Gómez Verdejo
Language
English
Attendance
On-campus
Credits
60
Campus
Leganes
Applications

 Opening December 1 

☛ Places available: 30

Double degree:  Opening February 15, 2023 

Departments
Signal and Communications Theory Department, Bioengineering and Aeroespace Engineering Department

MORE INFORMATION HERE

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APPLICATION FOR ADMISSION

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  • Inicio

    Changes pending approval for the 2023-2024 academic year

     

    The Master in Machine Learning and Health (formerly Master in Information Health Engineering) emerges as an answer to the increasing demand of researchers with an interdisciplinary background in the fields of machine learning and bioengineering. Nowadays, the intersection of these two areas stands out for its enormous potential in both research and application: the role of machine learning, signal processing, data science, and artificial intelligence is becoming crucial in almost any field and particularly in health applications. Significantly, both public and private investing in research related to these areas has an enormous social and economic impact. In fact, companies such as Philips, Siemens, Microsoft, IBM, Amazon, Google or Apple, to name just a few, are demanding this research profile.

    This Master combines the disciplines of machine learning and health with the goal of training researchers to become experts in signal and data analysis tools, with special emphasis on their use on medical signals and images. The training provided by the master's degree will have a strong theoretical foundation, which will provide future graduates with the necessary knowledge to start their subsequent doctoral studies and/or develop R&D activities in industry.

    Tratamiento de imágenes médicas

    razones para estudiar el master en Ingeniería de la Información para la salud

    │MASTER IN NUMBERS

    • ☛ Taught by more than 20 professors and leading researchers in the field
    • ☛ The program is completed in one academic year
    • ☛ According to Forbes two of the three most demanded jobs are related to AI and health
    • ☛ Personalized master program: an offer of 18 courses to adjust the program to your background and interests
  • CURRICULUM
    • CURRICULUM 23/24

      The program consists of 60 ECTS to be studied in 2 semesters with the following structure:

      SEMESTER 1 (30 ECTS)

      • SUBJECT 1 | BASIC FORMATION
        Formed by 3 compulsory subjects of 6 ECTS each.
      • SUBJECT 2 | METHODS AND TOOLS FOR COMPUTATIONAL INTELLIGENCE
        It contains 5 elective subjects of 6 ECTS each. Students must choose two of these five subjects.

      SEMESTER 2 (30 ECTS)

      • SUBJECT 3 | MEDICAL IMAGES AND VISION BY COMPUTER
        Composed of several elective subjects of 3 and 6 ECTS on the processing and analysis of data based on medical images.
      • SUBJECT 4 | LEARNING MACHINE IN HEALTH
        Composed of several elective subjects of 3 and 6 ECTS on  advanced methods of machine learning relevant in specific areas of health.
      • SUBJECT 5 | SKILLS FOR RESEARCH
        Formed by the subject Master Thesis of 12 ECTS.
      Formative Complements **
      Subjects ECTS TYPE Language
      Introduction to Biosignals and Bioimaging 3 FC Inglés
      Introduction to Machine Learning 2 FC Inglés
      Introduction to Statistical Signal Processing 2 FC Inglés

      Academic Year 1 - Semester 1

      Core Courses
      SubjectsECTSTYPELanguage
      Biosignals & Bioimages6CEnglish
      Machine Learning6CEnglish
      Statistical Signal Processing6CEnglish
      Methods and tools for computational intelligence
      SubjectsECTSTYPELanguage
      Choose 2
      Deep Learning6EEnglish
      Biomedical Image Processing6EEnglish
      Data Modelling6EEnglish
      Data intensive computing6EEnglish
      Optimization6EEnglish

      Academic Year 1 - Semester 2

      Medical imaging and computer vision*
      SubjectsECTSTYPELanguage
      Choose a minimum of 6 ECTS
      Medical image reconstruction6EEnglish
      Surgical navigation and imaging3EEnglish
      Neuroimaging3EEnglish
      Computer Vision6EEnglish
      Machine learning for health*
      SubjectsECTSTYPELanguage
      Choose a minimum of 6 ECTS
      Information Theory for Machine Learning6EEnglish
      Natural Language Processing3EEnglish
      Personalized medicine3EEnglish
      Speech technologies for health3EEnglish
      Artificial Intelligence in radiology and microscopy3EEnglish
      Research skills
      SubjectsECTSTYPELanguage
      Master Thesis12TFM

      Changes pending approval for the 2023-2024 academic year

       

      * To complete the 30 ETCS of the Semester 2, the students will study the 12 ECTS of subject-matter 5 and, in addition, they must choose a total of 18 ECTS between the subjects of the subject-matter 3 and 4, choosing a minimum of 6 ECTS in each subject-matter.
       

      ** Formative Complements: in general, according to the entry profile, the following is established:

      • Students coming from Data Science and Telecommunication Engineering degrees must take Subject 1.
      • Students coming from Bioengineering degrees must take Subjects 2 and 3.
      • Students coming from Computer Engineering degrees must take Subjects 1 and 3.

      The rest of the admission profiles must take the three training complements. However, the academic committee of the master's degree will be responsible for evaluating the profile of the students, considering the curriculum taught in the center of origin and the specific training of each one, and may assign in some cases additional complements or exempt the completion of some of them.

       

      C) Compulsory: 18 ECTS

      E) Elective course: 30 ECTS

      TFM) Master Thesis: 12 ECTS

    • CURRENT CURRICULUM

      The program consists of 60 ECTS to be studied in 2 semesters with the following structure:

      SEMESTER 1 (30 ECTS)

      • SUBJECT 1 | BASIC FORMATION
        Formed by 3 compulsory subjects of 6 ECTS each.
      • SUBJECT 2 | METHODS AND TOOLS FOR COMPUTATIONAL INTELLIGENCE
        It contains 4 elective subjects of 6 ECTS each. Students must choose two of these four subjects.

      SEMESTER 2 (30 ECTS)

      • SUBJECT 3 | MEDICAL IMAGES AND VISION BY COMPUTER
        Composed of several elective subjects of 3 and 6 ECTS on the processing and analysis of data based on medical images.
      • SUBJECT 4 | LEARNING MACHINE IN HEALTH
        Composed of several elective subjects of 3 and 6 ECTS on  advanced methods of machine learning relevant in specific areas of health.
      • SUBJECT 5 | SKILLS FOR RESEARCH
        Formed by the subject Master Thesis of 12 ECTS.

      Academic Year 1 - Semester 1

      Core Courses
      SubjectsECTSTYPELanguage
      Biosignals & Bioimages6CEnglish
      Machine Learning6CEnglish
      Statistical Signal Processing6CEnglish
      Methods and tools for computational intelligence
      SubjectsECTSTYPELanguage
      Choose 2
      Deep Learning6EEnglish
      Biomedical Image Processing6EEnglish
      Data Modelling6EEnglish
      Data intensive computing6EEnglish

      Academic Year 1 - Semester 2

      Medical imaging and computer vision*
      SubjectsECTSTYPELanguage
      Choose a minimum of 6 ECTS
      Medical image reconstruction6EEnglish
      Surgical navigation and imaging3EEnglish
      Neuroimaging3EEnglish
      Computer Vision6EEnglish
      Machine learning for health*
      SubjectsECTSTYPELanguage
      Choose a minimum of 6 ECTS
      Information Theory6EEnglish
      Natural Language Processing3EEnglish
      Optimization6EEnglish
      Personalized medicine3EEnglish
      Speech technologies for health3EEnglish
      Research skills
      SubjectsECTSTYPELanguage
      Master Thesis12TFM

      * To complete the 30 ETCS of the Semester 2, the students will study the 12 ECTS of subject-matter 5 and, in addition, they must choose a total of 18 ECTS between the subjects of the subject-matter 3 and 4, choosing a minimum of 6 ECTS in each subject-matter.
       

      C) Compulsory: 18 ECTS

      E) Elective course: 30 ECTS

      TFM) Master Thesis: 12 ECTS

      SUBJECTS NOT OFFERED | 22/23 ACADEMIC YEAR

       
      Subjects ECTS TYPE Language
      Medical image generation 3 OP Inglés
      Clinical data 3 OP Inglés
      Communication Technologies in Healthcare 3 OP Inglés
    • QUALITY

      GENERAL COURSE INFORMATION

      ☛ First year offered: 2019

      QUALITY INDICATORS

      Master's Degree indicators

      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 subjects and their faculty

  • FACULTY

    FACULTY

    The Master in Information Health Engineering has a teaching team of full professors and associate professors from the different Departments participating in the program:

     

    UC3M FACULTY

    • ABELLA GARCÍA, MÓNICA
      Department of Bioengineering and Aeroespace Engineering
      Associate Professor
      PhD / Engineer
      Brief CV
    • ARENAS GARCÍA, JERÓNIMO
      Department of Signal Theory and Communications
      Associate Professor
      ​PhD
      Brief CV
    • ARTÉS RODRÍGUEZ, ANTONIO
      Department of Signal Theory and Communications
      Full Professor
      PhD
      Brief CV
    • CID SUEIRO, JESÚS
      Department of Signal Theory and Communications
      Full Professor
      PhD
      Brief CV
    • CUSSÓ MULA, LORENA
      Department of Bioengineering and Aeroespace Engineering
      PhD Assistant Professor
      PhD
      Brief CV
    • DESCO MENÉNDEZ, MANUEL
      Department of Bioengineering and Aeroespace Engineering
      Full Professor
      PhD / Engineer
      Brief CV
    • DÍAZ DE MARÍA, FERNANDO
      Department of Signal Theory and Communications
      Full Professor
      PhD
      Brief CV
    • GONZÁLEZ DÍAZ, IVÁN
      Department of Signal Theory and Communications
      Associate Professor
      PhD
      Brief CV
    • GÓMEZ VERDEJO, VANESSA​
      Department of Signal Theory and Communications
      Associate Professor
      PhD
      Brief CV
    • KOCH, TOBIAS
      Department of Signal Theory and Communications
      Associate Professor
      ​PhD
      Brief CV
    • MARTÍNEZ OLMOS, PABLO​
      Department of Signal Theory and Communications
      Associate Professor
      PhD
      Brief CV
    • MÍGUEZ ARENAS, JOAQUÍN
      Department of Signal Theory and Communications
      Full Professor
      ​PhD
      Brief CV
    • MOLINA BULLA, HAROLD
      Department of Signal Theory and Communications
      Visiting Professor
      PhD
      Brief CV
    • MUÑOZ BARRUTIA, ARRATE
      Department of Bioengineering and Aeroespace Engineering
      Associate Professor
      PhD / Engineer
      Brief CV
    • PARRADO HERNÁNDEZ, EMILIO
      Department of Signal Theory and Communications
      Associate Professor
      PhD
      Brief CV
    • PASCAU GONZÁLEZ-GARZÓN, JAVIER
      Department of Bioengineering and Aeroespace Engineering
      Associate Professor
      PhD / Engineer
      Brief CV
    • PELÁEZ MORENO, CARMEN​
      Department of Signal Theory and Communications
      Associate Professor
      PhD
      Brief CV
    • RIOS MUÑOZ, GONZALO RICARDO
      Department of Bioengineering and Aeroespace Engineering
      Assistant Professor
      PhD
      Brief CV
    • RIPOLL LORENZO, JORGE
      Department of Bioengineering and Aeroespace Engineering
      Visiting Professor
      PhD
      Brief CV
    • VAQUERO LÓPEZ, JUAN JOSÉ
      Department of Bioengineering and Aeroespace Engineering
      Full Professor
      PhD / Engineer
      Brief CV
    • VÁZQUEZ VILAR, GONZALO
      Department of Signal Theory and Communications
      Associate Professor
      PhD
      Brief CV
  • ADMISSION
    • ADMISSION

      Application

      The request is made electronically through our application. Before starting the admission process, please, read the following information:

      REQUIREMENTS

      To access this master's degree, it is necessary to hold a degree in Telecommunications Engineering, Data Engineering and Data Science,  Computer Science and Computer Engineering, Electrical Engineering, Biomedical Engineering or Bioengineering

       

      FORMATIVE COMPLEMENTS

      Formative Complements are defined to facilitate the incorporation of students with different profiles, with emphasis on those profiles without knowledge of Bioengineering, Machine Learning and Statistics. It is a block composed of three courses with contents to acquire the necessary competences to start the master's program, which will be taken according to the profile and previous knowledge of the applicants.

       

      ADMISSION CRITERIA

      Candidate selection will be done on the basis of the following criteria:

      ADMISSION CRITERIA SCORING
      Academic record 60%
      Research experience 10%
      Grades in essential courses to the Master's programme 15%
      Motivation, interest and recommendation letters 10%
      Professional experience and other academic merits (awards, grants, international stays, etc.) 5%

      ADMISSION PROFILE

      The Master of Information Health Engineering is mainly aimed at engineering graduates of the following families:

      • Telecommunications Engineering
      • Data Engineering and Data Science
      • Computer Science and Computer Engineering
      • Electrical Engineering
      • Biomedical Engineering or Bioengineering

      or other related degrees such as mathematics or other engineering degrees

      Language requirements

      Check the general language requirements required to study a Master’s at UC3M, depending on whether it is in Spanish, English or bilingual.

      students with foreign university degrees

      Once admitted to the Master’s, students with university degrees issued by a higher education institution belonging to an educational system outside the EHEA, must provide, for enrolment, the diploma, legalized by diplomatic procedures or by means of The Hague Apostille. They must also submit the transcript of records, with the grade point average, duly legalized.

      More information about Legalization of Foreign Documents.

      If needed, documents must be accompanied by an official sworn translation into Spanish.

    • ENROLLMENT

      FEES*

      Reservation fee: €450 

      • it will be paid once the student receives notification of admission to the master’s, and deducted from the first tuition payment
      • the reservation fee will only be refunded if the master program is cancelled

      60 ECTS in the first academic year:

      • EU students: €2,701.2 (€45.02/ECTS credit)
      • Non EU students: €5,044.2 (€84.07/ECTS credit)

       

      ✎│Programme’s fees


      NOTE: The enrolment fees do not include the cost of issuing the master’s degree certificate.

      _______

      * Current fees for the 22/23 academic year, pending approval by the Community of Madrid for the 23/24 academic year.

      Additional information

      • You may enrol on the master’s degree after completing the admission process and receiving formal confirmation of your acceptance.
      • When performing the enrolment you can choose between Full-time enrolment or Part-time enrolment.
      • The email address provided upon enrolment will be used for formal communications; students are therefore kindly requested to check their mail regularly.
      • Pursuant to the regulations of the Universidad Carlos III de Madrid, a student failing to pay any part of the fees will not be admitted and the enrolment process will be terminated. In cases of cancellation of enrolment due to non-payment, the University may demand the payment of the pending amounts for enrolment in previous academic courses as a prior condition of enrolment.
        No diploma or certificate will be issued if a student has any outstanding payments.

      ✎│Enrolment master’s programmes

      ✎│ECTS credits recognition

  • SCHOLARSHIPS

    General information on scholarships

    For more information on specific scholarships of interest awarded by UC3M and by other agencies or organisations.

    🎓 │ Scholarships to study a University Master

  • PRACTICAL INFORMATION

    titulo cabecera para sección calendario académico

    Academic Calendar

    Academic Calendar 2022-2023

    titulo cabecera para sección horario del master

    MASTER’S COURSE SCHEDULE

    Check the Master’s schedule

    titulo cabecera para sección secretaría virtual

    VIRTUAL SECRETARIAT

    Access to Virtual Secretariat

    titulo cabecera para seccion recursos materiales del máeter

    MATERIAL RESOURCES OF THE PROGRAMME

    Material resources of Leganes Campus

    titulo cabecera para sección quejas, reclamaciones y sugerencias

    complaints and suggestions

    General Registry Office

    Contact mailbox 

  • DOUBLE DEGREE