Alumniprofile Health Care IT
Dr. Benjamin Eigl
The winner of the “MITAT Best Investigator Award” and Carinthian in exile – he currently lives in Bern – enjoys spending his free time playing sports…
This Master's program is organized in a work-friendly way and is therefore compatible with a professional career.
Health Care IT - Master's program
High-Tech in Medicine
The Master degree study program ‘Health Care IT’ addresses two important components that will fundamentally and sustainably shape the future of the current health system. This is particularly the use of artificial intelligence, which can support the process of assessing a diagnosis and the evaluation of imaging data, and it may also affect many other sectors that we are not even thinking about at the moment. Another important point that will affect the current health system is the aging of the population as a result of demographic change.
Technical aspects of Health Care IT
This master degree program focuses on these technical aspects of Health Care IT, by providing a specific education in deep learning and clinical data analysis as well as in 3D printing and robotics. Active and Assisted Living is another core element of the program that enables students to face the future challenges of the aging society today. Additional to theoretical input, students receive hands-on training in specialized laboratories. Small groups, personal support and mentoring, and an open door policy for all professors is a top priority.
Since internationalization is an important aspect of modern education, students are encouraged to go for an internship abroad and supported in joint projects with our research partners.
Study + Work
Study & Work - is that possible?
With over 60 Study & Work partner companies and organizations, Carinthia University of Applied Sciences offers first-year students of a bachelor's or master's degree program the opportunity to combine their studies with a career.
This attractive offer gives students the chance to immediately put theoretical knowledge into practice and gain professional experience in Carinthia's leading companies.
Information
Contact
If you have any questions feel free to contact:
Head of Degree Program
Level of qualification
Master
Master
ECTS credits
120
120
Tuition fees
€ 363.36 / semester
€ 363.36 / semester
Qualification awarded
- Master of Science in Engineering
Duration of study
4 semester
4 semester
ÖH (Austrian Student Union) fee
€ 21.20 / semester
€ 21.20 / semester
Language of instruction
Englisch
Englisch
FH campus
- Klagenfurt
General Study Information
Curriculum
Profile
The Master degree study program “Health Care IT” enables graduates to successfully face the challenges in the healthcare sector. Equipped with technical and medical knowledge they are sought-after by a wide variety of potential employers in the health care industry. The program also prepares them for upcoming social issues like Active and Assisted Living (AAL) and Instrumental Activities of daily Living (iADL), which become more and more important as we are moving towards an aging society.
Students benefit from practical trainings in dedicated laboratories and work there in small groups. Two areas of specialization allow them to further deepen their interests: Medical Engineering and Image Processing or Health Informatics can be chosen over the course of the degree program. Thanks to strong cooperation with the Health Care sector, the program is able to invite professionals and experts as guest lecturers.
The students of the School of Engineering & IT should demonstrate strengths in the following areas:
- technical understanding,
- reasoning power,
- good English, mathematics and computer skills,
- creativity,
- enjoyment of innovative developments.
Graduates of the master degree program Health Care IT are able to:
- comprehend, analyze and remodel processes in medicine, nursing and Management,
- develop and implement QM systems in healthcare,
- retrieve their detailed knowledge of the conception, design and functionality of healthcare information systems in order to design such Systems,
- describe the interaction of economics success, technology , processes and quality in healthcare,
- plan and use indicators for the implementation of corporate guidelines in the areas of procurement, planning an d development,
- present functioning, theoretical principles and technical implementation of medical devices,
- list application possibilities of mobile systems in healthcare and analyze, conceptualize and design applications of such Systems,
- design, implement and evaluate medical studies in cooperation with medic.
Current courses - Health Care IT
| Lecture | Type | SPPS | ECTS-Credits | Course number |
|---|---|---|---|---|
| Active Assisted Living 2 | ILV | 3,0 | 5,0 | M2.03100.20.010 |
| Applied Medical Image Analysis | ILV | 3,0 | 5,0 | M2.03100.20.030 |
| Artificial Neural Networks and Deep Learning (I) | ILV | 3,5 | 5,0 | M2.08760.11.131 |
| Augmented Visualization in Medicine | ILV | 3,0 | 5,0 | M2.03100.20.040 |
| Project (II) - Frameworks and Concept Study | PA | 3,0 | 5,0 | M2.03100.20.060 |
| Smart Medical Production and Robotics | ILV | 3,0 | 5,0 | M2.03100.20.050 |
| Lecture | Type | SPPS | ECTS-Credits | Course number |
|---|---|---|---|---|
| Master Thesis | MT | 0,5 | 25,0 | M2.03100.40.010 |
| Master Thesis Seminar HCIT | SE | 2,0 | 5,0 | M2.03100.40.281 |
| Master Thesis HCIT | MT | 0,0 | 25,0 | M2.03100.40.291 |
| Master Thesis Seminar | SE | 2,0 | 2,0 | M2.03100.40.020 |
| Lecture | Type | SPPS | ECTS-Credits | Course number |
|---|---|---|---|---|
| Academic Skills | SE | 3,0 | 5,0 | M2.08860.10.061 |
| Active Assisted Living 1 | ILV | 3,0 | 5,0 | M2.03100.10.010 |
| Applied Medical Signal Analysis | ILV | 3,0 | 5,0 | M2.03100.10.030 |
| Introduction to Machine Learning | ILV | 3,5 | 5,0 | M2.08760.11.051 |
| Project (I) - Prerequisites and Project Domains | PA | 3,0 | 5,0 | M2.03100.10.060 |
| Statistics | ILV | 3,5 | 5,0 | M2.08760.11.021 |
| Lecture | Type | SPPS | ECTS-Credits | Course number |
|---|---|---|---|---|
| Artificial Intelligence in Clinical Imaging | ILV | 3,0 | 5,0 | M2.03100.30.030 |
| Artificial Neural Networks and Deep Learning (II) | ILV | 3,5 | 5,0 | M2.08760.11.141 |
| Entrepreneurship | SE | 3,0 | 5,0 | M2.03100.30.040 |
| Neuroscience | ILV | 3,0 | 5,0 | M2.03100.30.050 |
| Project (III) - Practical Implementation | PA | 3,0 | 5,0 | M2.03100.30.060 |
| Studies in Biomedical Engineering | ILV | 3,0 | 5,0 | M2.03100.30.010 |
| Lecture | Type | SPPS | ECTS-Credits | Course number |
|---|---|---|---|---|
| Active Assisted Living 2 | ILV | 3,0 | 5,0 | M2.03100.20.010 |
| Applied Medical Image Analysis | ILV | 3,0 | 5,0 | M2.03100.20.030 |
| Artificial Neural Networks and Deep Learning (I) | ILV | 3,5 | 5,0 | M2.08760.11.131 |
| Augmented Visualization in Medicine | ILV | 3,0 | 5,0 | M2.03100.20.040 |
| Project (II) - Frameworks and Concept Study | PA | 3,0 | 5,0 | M2.03100.20.060 |
| Smart Medical Production and Robotics | ILV | 3,0 | 5,0 | M2.03100.20.050 |
| Lecture | Type | SPPS | ECTS-Credits | Course number |
|---|---|---|---|---|
| Master Exam | ME | 0,0 | 3,0 | M2.03100.40.030 |
| Master Thesis | MT | 0,5 | 25,0 | M2.03100.40.010 |
| Master Thesis Seminar | SE | 2,0 | 2,0 | M2.03100.40.020 |
| Lecture | Type | SPPS | ECTS-Credits | Course number |
|---|---|---|---|---|
| Academic Skills | SE | 3,0 | 5,0 | M2.08860.10.061 |
| Active Assisted Living 1 | ILV | 3,0 | 5,0 | M2.03100.10.010 |
| Applied Medical Signal Analysis | ILV | 3,0 | 5,0 | M2.03100.10.030 |
| Introduction to Machine Learning | ILV | 3,5 | 5,0 | M2.08760.11.051 |
| Project (I) - Prerequisites and Project Domains | PA | 3,0 | 5,0 | M2.03100.10.060 |
| Statistics | ILV | 3,5 | 5,0 | M2.08760.11.021 |
| Lecture | Type | SPPS | ECTS-Credits | Course number |
|---|---|---|---|---|
| Artificial Intelligence in Clinical Imaging | ILV | 3,0 | 5,0 | M2.03100.30.030 |
| Artificial Neural Networks and Deep Learning (II) | ILV | 3,5 | 5,0 | M2.08760.11.141 |
| Entrepreneurship | SE | 3,0 | 5,0 | M2.03100.30.040 |
| Neuroscience | ILV | 3,0 | 5,0 | M2.03100.30.050 |
| Project (III) - Practical Implementation | PA | 3,0 | 5,0 | M2.03100.30.060 |
| Studies in Biomedical Engineering | ILV | 3,0 | 5,0 | M2.03100.30.010 |
Research in the study program
Research and development make an important contribution to transforming broad university knowledge into practical application solutions and to promoting cooperation between companies and universities.
- Click directly to the Research Groups AAL and ADMiRE
- Click directly to the Research Center CisMAT
- More information to the Equipment and Measurement Labs
- More information to the Research groups and research projects
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Job & Career
The Master of Science “Health Care IT” degree program is designed to educate and train highly qualified specialists in the areas of new health technologies and data intelligence.
Graduates have a therefore a wide spectrum of excellent and exciting career opportunities in fields such as:
- Research and Development
- Hospital Information Technology
- Software Development and Consulting
- Active and Assisted Living
- Biomedical Engineering / Medical Device Development
- Medical Image Processing
The successful completion of the master program in turn qualifies the graduate to undertake a doctorate.
Career Profiles
Alumniprofile Health Care IT
Dipl.-Ing. Ivan Knezevic, BSc.
Ivan Knezevic studied Medical Engineering as part of his Bachelor’s degree at Carinthia University of Applied Sciences. In 2016, he successfully…
Alumniprofile Health Care IT
Elena Oberrauner, BSc
Diagnosen und Behandlungen im medizinischen Kontext benötigen heutzutage bereits vielfältige technische Unterstützung zur Gewährleistung eines…
Statements
Faculty and Staff - Health Care IT
Program Director Medical Engineering
FH-Prof. Priv.-Doz. Dipl.-Ing. (FH)
Günther Grabner, Ph.D.
Student Support Services
Erika Gamnig
Claudia Palank
Program Director Multimedia Technology
Dipl.-Ing.
Jürgen Thierry
Professor of English
Marvin Hoffland, MSc.
+43 (0)5 90500-3215
m.hoffland[at]fh-kaernten[dot]atHomepage Primoschgasse 10
9020 Klagenfurt am Wörthersee
m.hoffland[at]fh-kaernten[dot]atHomepage Primoschgasse 10
9020 Klagenfurt am Wörthersee
Professor of Data Science
FH-Prof. DI (FH) Dr. techn.
Markus Prossegger
Professor of Computer Science
FH-Prof. Dipl.-Ing. Dr. techn.
Dominik Rauner-Reithmayer
+43 (0)5 90500-3212
d.rauner-reithmayer[at]fh-kaernten[dot]at Primoschgasse 10
9020 Klagenfurt am Wörthersee
d.rauner-reithmayer[at]fh-kaernten[dot]at Primoschgasse 10
9020 Klagenfurt am Wörthersee
Senior Lecturer1
FH-Prof.in Dr.in rer. nat. Priv.-Doz. DI Mag.a
Anita Kloss-Brandstätter
Professor for Computer Graphics & Augmented Reality
DI Dr. techn.
Andreas Daniel Hartl
Professor of Robotics
FH-Professorin Dr.in
Lisa-Marie Faller, BSc MSc
Endowed Professorship Smart Materials/Industry 4.0
FH-Prof. Dr. habil.
Pascal Nicolay
Senior Researcher/Lecturer
Dipl.-Ing.
Verena Venek, BSc
Project Assistant
Amin Fakia, BSc
Part-time Lecturer
FH-Prof. Dipl.-Ing. Dr. techn.
Pierre Elbischger
Mag. Dr.
Florian Fischmeister
DI
Stanislav Motyka
Campus
Campus Klagenfurt – Primoschgasse
Primoschgasse 8-10
9020 Klagenfurt am Wörthersee, Austria
+43 5 90500 3301
klagenfurt[at]fh-kaernten[dot]at
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