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.

 

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

* Change of the name from Health Care IT to Medical Engineering and Analytics, subject to the decision of the Board of AQ Austria pursuant to section 14 sub-section 2 no 1 FH-AkkVO 2021

 

Application deadline

Winterm 2023

Period I: 01.11.-15.03.2023
Period II: 16.03.-15.05.2023
Period III: 16.05.-15.07.2023
Period IV: 16.07.-30.09.2023*

For applicants from outside Europe applications are only accepted within Period I & II (due to Visa Processing)

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

Study start

The Semester starts in the week of 1 october

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.

Campus Day
03.03.2023
15-18 h

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

Further information

• 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, application examples, etc. are made available by the provided by the teachers.

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
ECTS credits
120
Tuition fees
€ 363.36 / semester
Qualification awarded
  • Master of Science in Engineering
Duration of study
4 semester
ÖH (Austrian Student Union) fee
€ 21.20 / semester
Language of instruction
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

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
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
LectureTypeSPPSECTS-CreditsCourse 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
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 Project 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
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
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
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
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 Project 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
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.

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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

Foto von Benjamin Eigl
alt text
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…

Dipl.-Ing. Ivan Knezevic, BSc.
alt text
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.

alt text
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…

Photo Michael Allmayer
alt text
Alumniprofile Health Care IT

Dipl.-Ing. Michael Allmayer, BSc

IT-Systems-Engineer, KABEG

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
Senior Researcher

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
Senior Researcher/Lecturer

Dipl.-Ing.

 Verena Venek, BSc
+43 (0)5 90500-3218
v.venek[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 Innovation Management Entrepreneurship

FH-Prof. DI Dr.

 Josef Tuppinger
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

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

 Michael Roth
Project Assistant
 Amin Fakia, BSc
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

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

 Pierre Elbischger

Mag. Dr.

 Florian Fischmeister
 Dinesh PUNNI

Campus

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9020 Klagenfurt am Wörthersee, Austria
+43 5 90500 3301
klagenfurt[at]fh-kaernten[dot]at

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