TECH Scholarship for Master's Students
from Europe, South America & Mexico


The Carinthian University of Applied Sciences is offering a new TECH Scholarship for Master Students from Europe, South America & Mexico.

In order to inspire new and talented students from Europe, South America & Mexico to pursue a master's degree in Austria, the Carinthian University of Applied Sciences (CUAS) | FH Kärnten (in collaboration with companies and associations) is offering four scholarships of 8,400 euros each.
 

Master program Medical Engineering and Analytics

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 and 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 and 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 and 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.

Application deadline

Winterterm 2025
Period I: 01.11.-15.03.2025
Period II: 16.03.-15.05.2025
Period III: 16.05.-15.07.2025
Period IV: 16.07.-30.09.2025* 

For applicants from outside Europe applications are only accepted within Period I.

*We reserve the right not to open the period or to close it early.

Study start

The semester starts in October - we only offer intake in winterterm!


The start of lectures can be found in the individual timetable which is available after enrollment.

Teaching time

Monday - Thursday from 15:00h
Friday from 13:30 h

Approx. 2-3 Saturdays/semester

Hybrid participation either on-site or online and partially HyFlex

Events

Study Guidance

Book your personal appointment right now!

You can find out more about our advisory services, events and fairs on our website.

Further information

Language of Instruction: English
Minimum of higher intermeidate B2, stated by either IELTS, TOEFL or Cambridge English Qualifications Certificate

Admission requirements:
Please note that foreign educational documents need to be legalized as well as translated in order to apply.
- the 1st online master's degree program in the field of engineering & IT
- HyFlex => Extension of the blended learning
- flexible and independent study in terms of time and place
- students can choose whether to take classes synchronously or asynchronously
- the course of study is a response to the increasing heterogeneity of students
- learning material, examples, etc. are made available by the teachers.

Study + Work

With over 100 Study & Work partner companies and organizations, CUAS offers students the opportunity to combine studying and working!

Study & Work for full-time students

  • Extent of employment: marginally up to 8h / week possible
  • Timetable: Some degree courses are organized so that Monday is a day off.

Study & Work for part-time students

  • Scope of employment: part-time up to max. 20h / week possible
  • The timetable is organized in a work-friendly way (lectures at the end of the day, weekend, blocked or online).

Medical Engineering and Analytics - Information

Contact

If you have any questions feel free to contact:

Head of Degree Program

 

 

Level of qualification
Master
ECTS credits
120.00
Tuition fees
€ 363.36 / semester
Qualification awarded
  • Master of Science in Engineering
Duration of study
4 semester
ÖH (Austrian Student Union) fee
€ 24.70 / semester
Language of instruction
English
FH campus
  • Klagenfurt

General Study Information

 

 

 

 

 

 

 

 

Curriculum - Medical Engineering and Analytics

Profile of the study program Medical Engineering and 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.

A Bachelor's degree in a relevant field such as medical technology, biomedical engineering, medical informatics or data science is required to be eligible. 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

LectureTypeSPPSECTS-CreditsCourse 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
Augmented Visualization in Medicine ILV 3,0 5,0 M2.03100.20.040
Data Analytics and Neural Networks ILV 3,0 5,0 M2.03100.20.020
Project (II) - Frameworks and Concept Study PA 0,3 5,0 M2.03100.20.060
Smart Medical Production and Robotics ILV 3,0 5,0 M2.03100.20.050
LectureTypeSPPSECTS-CreditsCourse 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
LectureTypeSPPSECTS-CreditsCourse 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
Augmented Visualization in Medicine ILV 3,0 5,0 M2.03100.20.040
Data Analytics and Neural Networks ILV 3,0 5,0 M2.03100.20.020
Project (II) - Frameworks and Concept Study PA 0,3 5,0 M2.03100.20.060
Smart Medical Production and Robotics ILV 3,0 5,0 M2.03100.20.050
LectureTypeSPPSECTS-CreditsCourse 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
LectureTypeSPPSECTS-CreditsCourse 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 Domains PA 3,0 5,0 M2.03100.10.060
Statistics ILV 3,5 5,0 M2.08760.11.021
LectureTypeSPPSECTS-CreditsCourse number
Artificial Intelligence in Clinical Imaging ILV 3,0 5,0 M2.03100.30.030
Deep Learning in Medical Applications ILV 3,0 5,0 M2.03100.30.020
Entrepreneurship SE 3,0 5,0 M2.03100.30.040
Neuroscience ILV 3,0 5,0 M2.03100.30.050
Project (III) - Pracical Implementation PA 0,3 5,0 M2.03100.30.060
Studies in Biomedical Engineering ILV 3,0 5,0 M2.03100.30.010
LectureTypeSPPSECTS-CreditsCourse number
Active Assisted Living 2 ILV 3,0 5,0 M2.03100.20.010
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
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
Augmented Visualization in Medicine ILV 3,0 5,0 M2.03100.20.040
Data Analytics and Neural Networks ILV 3,0 5,0 M2.03100.20.020
Project (II) - Frameworks and Concept Study PA 3,0 5,0 M2.03100.20.060
Project (II) - Frameworks and Concept Study PA 0,3 5,0 M2.03100.20.060
Smart Medical Production and Robotics ILV 3,0 5,0 M2.03100.20.050
Smart Medical Production and Robotics ILV 3,0 5,0 M2.03100.20.050
LectureTypeSPPSECTS-CreditsCourse 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
LectureTypeSPPSECTS-CreditsCourse number
Active Assisted Living 2 ILV 3,0 5,0 M2.03100.20.010
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
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
Augmented Visualization in Medicine ILV 3,0 5,0 M2.03100.20.040
Data Analytics and Neural Networks ILV 3,0 5,0 M2.03100.20.020
Project (II) - Frameworks and Concept Study PA 3,0 5,0 M2.03100.20.060
Project (II) - Frameworks and Concept Study PA 0,3 5,0 M2.03100.20.060
Smart Medical Production and Robotics ILV 3,0 5,0 M2.03100.20.050
Smart Medical Production and Robotics ILV 3,0 5,0 M2.03100.20.050
LectureTypeSPPSECTS-CreditsCourse 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
LectureTypeSPPSECTS-CreditsCourse number
Academic Skills SE 3,0 5,0 M2.08860.10.061
Academic Skills SE 3,0 5,0 M2.08860.10.061
Active Assisted Living 1 ILV 3,0 5,0 M2.03100.10.010
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
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
Introduction to Machine Learning ILV 3,5 5,0 M2.08760.11.051
Project (I) - Prerequisites and Domains PA 3,0 5,0 M2.03100.10.060
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
Statistics ILV 3,5 5,0 M2.08760.11.021
LectureTypeSPPSECTS-CreditsCourse number
Artificial Intelligence in Clinical Imaging ILV 3,0 5,0 M2.03100.30.030
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
Deep Learning in Medical Applications ILV 3,0 5,0 M2.03100.30.020
Entrepreneurship SE 3,0 5,0 M2.03100.30.040
Entrepreneurship SE 3,0 5,0 M2.03100.30.040
Neuroscience ILV 3,0 5,0 M2.03100.30.050
Neuroscience ILV 3,0 5,0 M2.03100.30.050
Project (III) - Pracical Implementation PA 0,3 5,0 M2.03100.30.060
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
Studies in Biomedical Engineering ILV 3,0 5,0 M2.03100.30.010
LectureTypeSPPSECTS-CreditsCourse number
Academic Skills SE 3,0 5,0 M2.08860.10.061
Academic Skills SE 3,0 5,0 M2.08860.10.061
Active Assisted Living 1 ILV 3,0 5,0 M2.03100.10.010
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
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
Introduction to Machine Learning ILV 3,5 5,0 M2.08760.11.051
Project (I) - Prerequisites and Domains PA 3,0 5,0 M2.03100.10.060
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
Statistics ILV 3,5 5,0 M2.08760.11.021
LectureTypeSPPSECTS-CreditsCourse number
Artificial Intelligence in Clinical Imaging ILV 3,0 5,0 M2.03100.30.030
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
Deep Learning in Medical Applications ILV 3,0 5,0 M2.03100.30.020
Entrepreneurship SE 3,0 5,0 M2.03100.30.040
Entrepreneurship SE 3,0 5,0 M2.03100.30.040
Neuroscience ILV 3,0 5,0 M2.03100.30.050
Neuroscience ILV 3,0 5,0 M2.03100.30.050
Project (III) - Pracical Implementation PA 0,3 5,0 M2.03100.30.060
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
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.

Job & Career

The Master of Science “Medical Engineering and Analytics” degree program is designed to educate and train highly qualified specialists in the areas of new health technologies and data intelligence.

Medical Engineering and 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

Simone Schanitz

Simone Schanitz was already very interested in science and mathematics when she was at school. That's why it wasn't difficult for her to choose a…

Foto von Benjamin Eigl

Dr. Benjamin Eigl

Nach der Matura wollte Benjamin Eigl eigentlich in ein Medizinstudium inskribieren, aber nachdem ihm der technische Aspekt neben der Medizin ebenso…

Dipl.-Ing. Ivan Knezevic, BSc.

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.

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.
+43 (0)5 90500-3582
g.grabner[at]fh-kaernten[dot]at

Primoschgasse 10
9020 Klagenfurt am Wörthersee
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
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
Professor of Data Science

FH-Prof. DI (FH) Dr. techn.

 Markus Prossegger
+43 (0)5 90500-3148
m.prossegger[at]fh-kaernten[dot]at

Primoschgasse 8
9020 Klagenfurt am Wörthersee
Professor for Medical Informatics

FH-Prof.in Dipl.-Ing. Dr. techn.

 Daniela Elisabeth Ströckl, BSc
+43 (0)5 90500-3266
d.stroeckl[at]fh-kaernten[dot]at

Primoschgasse 10
9020 Klagenfurt am Wörthersee
Administration of Studies
 Alexandra Reithofer
Senior Lecturer1

FH-Prof. Dr. phil.

 Colin Heller, M.A.

FH-Prof.in Priv.-Doz. DI Mag.a Dr.in rer. nat.

 Anita Kloss-Brandstätter
Professor for Innovation Management Entrepreneurship

FH-Prof. DI Dr.

 Josef Tuppinger
Professorship for Applied Physics and Sensor Technology

FH-Prof. Dr. habil.

 Pascal Nicolay
Professor for Computer Graphics & Augmented Reality

DI Dr. techn.

 Andreas Daniel Hartl
Professor of Geoinformatics

FH-Prof. Dr.-Ing.

 Karl-Heinrich Anders
Professur für Robotik und mechatronische Systeme

Dipl.-Ing. Dr. techn.

 Mathias Brandstötter
International Relations Coordinator
 Stefanie Steiner, BA B.Ed M.A.
Senior Researcher

Dipl.-Ing. (FH) Mag. (FH)

 Michael Roth
Research Assistant
 Sutatip Pittayapong, MSc
Junior Researcher
 Maja Cetic, BSc MAS
+43 (0)5 90500-2162
m.cetic[at]fh-kaernten[dot]at

Primoschgasse 8
9020 Klagenfurt am Wörthersee
Project Staff
 Letícia Cotinguiba Silva
+43 (0)5 90500-3230
l.cotinguibasilva[at]fh-kaernten[dot]at

Primoschgasse 10
9020 Klagenfurt am Wörthersee
 Valentina Clara Peternell, BSc
+43 (0)5 90500-3213
v.peternell[at]fh-kaernten[dot]at

Primoschgasse 10
9020 Klagenfurt am Wörthersee
Project Assistant
 Clara Bauer, BSc
+43 (0)5 90500-3224
c.bauer[at]fh-kaernten[dot]at

Primoschgasse 10
9020 Klagenfurt am Wörthersee
 Amin Fakia, BSc MSc
Laboratory Engineer

DI

 Beáta Bachratá, Ph.D.
+43 (0)5 90500-3221
b.bachrata[at]fh-kaernten[dot]at

Primoschgasse 10
9020 Klagenfurt am Wörthersee
Part-time Lecturer

DI Dr.in techn.

 Olivia Pfeiler

Mag. DI Dr. techn.

 Kathrin Plankensteiner

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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