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.
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.
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 - 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.
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:
Graduates of the master degree program Health Care IT are able to:
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 |
---|---|---|---|---|
3D Reconstruction | ILV | 3,0 | 5,0 | M2.03100.30.581 |
Academic Writing for Graduate Students | SE | 2,0 | 3,0 | M2.03100.30.211 |
Medical Application | PT | 3,0 | 6,0 | M2.03100.30.601 |
Robotics and Prosthetics in Medicine | VO | 3,0 | 5,0 | M2.03100.30.591 |
Studies in Biomedical Engineering | ILV | 2,0 | 3,0 | M2.03100.30.611 |
Specialization Area: Health Informatics | Type | SPPS | ECTS-Credits | Course number |
Development of Mobile Applications | ILV | 3,0 | 4,0 | M2.03101.30.621 |
Specialization Area: Medical Engineering and Image Processing | Type | SPPS | ECTS-Credits | Course number |
Advanced Medical Devices | ILV | 3,0 | 4,0 | M2.03102.30.641 |
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 |
Research and development make an important contribution to transforming broad university knowledge into practical application solutions and to promoting cooperation between companies and universities.
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:
The successful completion of the master program in turn qualifies the graduate to undertake a doctorate.
FH-Prof. Priv.-Doz. Dipl.-Ing. (FH)
Günther Grabner, Ph.D.Dipl.-Ing.
Jürgen ThierryFH-Prof. DI (FH) Dr. techn.
Markus ProsseggerFH-Prof. Dipl.-Ing. Dr. techn.
Dominik Rauner-ReithmayerFH-Prof.in Dr.in rer. nat. Priv.-Doz. DI Mag.a
Anita Kloss-BrandstätterDI Dr. techn.
Andreas Daniel HartlFH-Professorin Dr.in
Lisa-Marie Faller, BSc MScFH-Prof. Dr. habil.
Pascal NicolayFH-Prof. Dipl.-Ing. Dr. techn.
Pierre ElbischgerProf. D.Sc.
Roman Kamnik, B.Sc. M.Sc.ao.Univ.-Prof. DI Dr.
Robert SablatnigDipl.-Ing. Dr.
Michael Seger-CandussiPrimoschgasse 8-10
9020 Klagenfurt am Wörthersee, Austria
+43 5 90500 3301
klagenfurt[at]fh-kaernten[dot]at
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