Alumniprofile Health Care IT
Dr. Benjamin Eigl
After finishing the MSc program in Health Care IT, he enrolled in the industrial PhD program from CASCINATION in Bern, where he is now working as a…
Medical Engineering & Analytics - Master
Medical Engineering & Analytics - Master's program
High-tech in medical engineering and analytics
Medical engineering is a recently emerged field that applies engineering, physics, mathematics, and computer science to health care in order to improve diagnostic tools, monitoring techniques, and therapeutic devices. The field of medical engineering is heavily involved in research and development and covers topics from tissue engineering and robotics, to development of medical devices and wearable sensors. The analytics field aims to find patterns in data to allow the automatization of the data processing and, thus, diagnostic assessment. These developments play a role as a major game-changer in our healthcare system and thus in our society.
Focus of the master´s program Medical Engineering & Analytics
The master of science program "Medical Engineering and Analytics" is designed to educate a new generation of medical engineers, who will innovate the healthcare systems of the future. The MSc program puts the main emphasis on the current trends in medical engineering –the use of artificial intelligence (AI), augmented and virtual reality (VR, AR), and as a result of the demographic change, assistive technologies.
AI already supports the evaluation of medical data and images nowadays, and in the future, it may also affect many other areas that we are not yet aware of. AR is being used for the teaching of medical doctors or for surgery planning but still requires more profound development to reach its full potential. The aging of the population is another important point shaping the future of healthcare systems worldwide and leads to vast developments and increased use of assistive technologies. With the main focus on these current trends, the MSc degree program in Medical Engineering & Analytics encompasses several courses with the topics deep learning, signal and image analysis, visualization, and assisted living. We also focus on entrepreneurship and provide the students with resources and assistance to found their own startups.
Additionally to theoretical input, hands-on training in specialized laboratories and work on projects represent other core elements of this MSc program. Due to close cooperation with the healthcare sector, healthcare professionals and experts can be invited as guest lecturers. Small groups, personal support and mentoring, and an open-door policy for all professors are our top priorities. Since internationalization is an important aspect of modern education, the students are encouraged and supported to go for an internship abroad in joint projects with our research partners.
Graduates of the Medical Engineering & Analytics master of science program have a wide spectrum of exciting career opportunities, often finding employment in medical device production companies, software development companies, hospitals, cutting-edge start-ups or as entrepreneurs themselves.
study hyflex (online)
Are you interested in studying “Medical Engineering and Analytics” online while maintaining the highest standards? Our HyFlex MSc program in “Medical Engineering and Analytics” allows you to study online with the possibility to do some lectures asynchronously at your own schedule and pace. Therefore, you can study from anywhere in the world and also combine the studies with your work and family life. We ensure the highest European educational standards at low tuition fees.
study work-friendly
Are you interested in studying Medical Engineering and Analytics on-site but want to work part-time as well? The MSc program in “Medical Engineering and Analytics” is designed in a work-friendly way with the lectures given in the afternoon and on 2-3 Saturdays per semester.
study & work
This program offers our students the chance to work part-time at one of our partner companies. With partner companies such as KABEG (Carinthia Hospital Management Company), PCS Professional Clinical Software and SOT Medical Systems, this program allows the students to gain professional experience in Carinthia's leading companies already during their studies.
100% ONLINE possible
This Master's program is organized in a work-friendly way and is therefore compatible with a professional career –> study onsite, online and/or even asynchronously
Carinthia University of Applied Sciences (CUAS) has been an associate member of the European University ATHENA, an excellence program of the European Commission, since 1 January 2023.
Study + Work
Study & Work - is that possible?
With over 80 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.
Medical Engineering & Analytics - 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
€ 22.70 / semester
€ 22.70 / semester
Language of instruction
Englisch
Englisch
FH campus
- Klagenfurt
General Study Information
Curriculum - Medical Engineering and Analytics
Profile of the study program Medical Engineering & Analytics
The Master of Science degree study program"Medical Engineering and Analytics" enables graduates to face the challenges of the modern healthcare sector. Equipped with knowledge of artificial intelligence, extended reality, and assistive technologies, graduates are sought-after by a wide variety of potential employers inside the health care industry as well outside of it.
Thanks to the Study & Work program, students can gain professional experience at Carinthia's leading companies already during their studies, ensuring a position for the vast majority of our graduates. Alternatively, the graduates of the MSc degree program "Medical Engineering and Analytics" can use their knowledge to pursue further scientific specialization in the form of a PhD or, due to the focus on entrepreneurship and assistance provided by CUAS, to found their own startups.
The prerequisite for attending the master of science degree course is a technical bachelor of science, a diploma engineer degree or another relevant undergraduate degree. Additionally, potential students should demonstrate strengths in the following areas:
- technical understanding and logical thinking,
- mathematics and computer skills,
- English,
- creativity and enjoyment of innovative developments,
- independent work.
Graduates of the master of science degree program Medical Engineering and Analytics are able to:
- understand the theoretical principles and technical implementation of medical applications,
- design, implement and evaluate studies in the medical engineering field,
- use artificial intelligence to solve complex problems,
- innovate and develop the medical engineering sector,
- communicate scientific and engineering ideas and results to the broader public,
- foster communication between medical staff and engineers,
- gain and apply new knowledge using appropriate learning strategies.
Current courses - Medical Engineering and Analytics
| 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 |
| 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 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 “Medical Engineering & Analytics” degree program is designed to educate and train highly qualified specialists in the areas of new health technologies and data intelligence.
Medical Engineering & Analytics 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 of science program qualifies graduates to undertake a doctorate.
Career Profiles
Alumniprofile Health Care IT
Dipl.-Ing. Ivan Knezevic, BSc.
While studying for his MSc degree in Health Care IT, he took advantage of the work-friendly study arrangement and started his career at PCS.
Alumniprofile Health Care IT
Elena Oberrauner, BSc
Nowadays, diagnoses and treatments in the medical context already require diverse technical support to ensure a high-quality healthcare system.
The…
Statements
Staff
Faculty and Staff - Medical Engineering and Analytics
Head of Degree Program "Medical Engineering & Analytics", Program Director of "Medical Engineering"
FH-Prof. Priv.-Doz. Dipl.-Ing. (FH)
Günther Grabner, Ph.D.
Administration of Studies
Mag.a
Michaela Filippitsch
+43 (0)5 90500-3101
m.filippitsch[at]fh-kaernten[dot]at Primoschgasse 10
9020 Klagenfurt am Wörthersee
m.filippitsch[at]fh-kaernten[dot]at Primoschgasse 10
9020 Klagenfurt am Wörthersee
Professor Ambient Assisted Living
FH-Prof. DI Dr.
Johannes Oberzaucher
+43 (0)5 90500-3234
j.oberzaucher[at]fh-kaernten[dot]at Primoschgasse 10
9020 Klagenfurt am Wörthersee
j.oberzaucher[at]fh-kaernten[dot]at Primoschgasse 10
9020 Klagenfurt am Wörthersee
Professor of Data Science
FH-Prof. DI (FH) Dr. techn.
Markus Prossegger
Senior Researcher
FH-Prof.in Dipl.-Ing. Dr. techn.
Daniela Elisabeth Ströckl, BSc
Senior Researcher/Lecturer
Dipl.-Ing.
Verena Venek, BSc
Senior Lecturer1
FH-Prof.in Dr.in rer. nat. Priv.-Doz. DI Mag.a
Anita Kloss-Brandstätter
Professor for Innovation Management Entrepreneurship
FH-Prof. DI Dr.
Josef Tuppinger
Professur für Robotik und mechatronische Systeme
Dipl.-Ing. Dr. techn.
Mathias Brandstötter
Endowed Professorship Smart Materials/Industry 4.0
FH-Prof. Dr. habil.
Pascal Nicolay
Senior Researcher
Dipl.-Ing. (FH) Mag. (FH)
Michael Roth
Senior Researcher/Lecturer
Lukas Wohofsky, BSc MSc
Project Assistant
Amin Fakia, BSc
Laboratory Engineer
DI
Beáta Bachratá, Ph.D.
Part-time Lecturer
FH-Prof. Dipl.-Ing. Dr. techn.
Pierre Elbischger
Mag. Dr.
Florian Fischmeister
DI
Stanislav Motyka
Dinesh PUNNI
Dr. med.
Lars Riedemann
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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