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Applied Natural Sciences, Department

Fakultät Elektrotechnik und Wirtschaftsingenieurwesen

Hochschule für angewandte Wissenschaften Landshut

Fakultät Elektrotechnik und Wirtschaftsingenieurwesen
Am Lurzenhof 1
D-84036 Landshut
Telephone: +49 871 506-0
https://www.haw-landshut.de

HAW Landshut
Department on the internet
Online application
Student body

Degree courses with details

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  • Department

Basic information

Percentage of teaching by practitioners

13.0%

Support during the study entry phase

Total score for support in the study entry phase

11/14 points

Job market- and career-orientation

Bachelor theses in cooperation with work environment

53.4%

Research

Cooperative doctoral degrees (in three years)

no data

Third party funds per professor

44,600 €

Further information provided by the department

Special features regarding teaching

Actively promoted start of studies through link programmes; Broad range of tutorials; Exercises and internships in small groups; Internships right from the first semester; Modern catalogue of compulsory elective subjects (robotics, machine learning...); State-of-the-art, programme-specific laboratories (medical imaging, bioanalytics, medical device technology, VR&AI laboratory); Very technical qualification with the ability to directly follow up with a Master’s degree programme in electrical engineering or a Master’s degree programme in Applied Research in Engineering Sciences

Special features regarding the international orientation

Four international advisers and the university’s International Office help students in their search for practical semesters, final dissertations or study visits abroad. The department supports and organises short-term stays abroad, such as summer schools or excursions, and is engaged in an intensive cooperation with STIEI Shanghai with regard to an internship abroad in Shanghai, China. Partner universities include Shanghai Normal University (China), Clemson University (USA), Vancouver Island University (Canada) and many others.; Financial support of foreign guest lecturers, including for online instruction

Special features regarding the equipment

Modern and very well-equipped laboratories: Medical engineering (specifically imaging and minimally invasive procedures), medical appliance engineering (set-up and testing of autonomous embedded systems, safety testers and monitor systems), bioanalytics and sensor technology (in-vitro diagnostics and clinical chemistry), laser and optical measurement technology, development and application of VR & AI; Electric hybrid circuits (possibility of internal production of electronic assemblies in small series); Databases:IEE Xplore, Perinorm, SpringerLink, wti, DEPATISnet, Statista, VDE Normenbibliothek, Wiley Online Library and much more

Special features regarding research and development

Project: NeuroTEST; Description: Stress tests of AI models for medical image data processing using synthetic and simulated MRI data; Duration: 24 months; Start: 01.01.2021; Industry partners: deepc GmbH, Munich; Project name: Deep-PPG; Description: Robust acquisition of the photoplethysmographic curve in mobile systems; Duration: 36 months; Start: 01.01.2021; Industry partners: Osram Opto Semiconductors GmbH; Independent research focus on medical engineering with the core topics of bioanalytics, imaging and image processing, workflow&IT, AI&VR

Other special features

Internal research projects can also be carried in cooperation with industry at the level of project work and final dissertations; Access to expertise and infrastructure of all laboratories of the Department of Electrical Engineering and Industrial Engineering; Psychological support offered for students with anxiety and psychological stress

Further information on research activities

Further information about study entry phase

Medical technology

Facts

Total number of students at the department

160

Students' assessments on undergraduate, presence-learning-courses

Teacher support
Support in studies

no data

Not specified
Courses offered

no data

Not specified
Study organisation
Exam organisation

no data

Not specified
Digital teaching elements

no data

Not specified
Laboratory internships

no data

Not specified
Offers for career orientation

no data

Not specified
Support during practical semester

no data

Not specified
Rooms

no data

Not specified
Library

no data

Not specified
IT-infrastructure

no data

Not specified
Overall study situation

no data

Not specified
Return rate of the questionnaires

17

Legend

Groups

green

top group

yellow

middle group

blue

bottom group
Not specified
not specified

Acronyms

(S) = Students' judgements

(F) = Facts

(P) = Professors' judgements

MT = Medical technology

Units

Value in percent

Value in points

Euro

Thousand Euro

Last Update 2022: Data collected by the CHE Center for Higher Education
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