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Digital Engineering
Bachelor of Science (B.Sc.)

The Faculty of Science and Technology (Faculty IV) at the University of Siegen offers three digital engineering degree programs in cooperation:

  • Digital Engineering - Mechanical Engineering
  • Digital Engineering - Electrical Engineering
  • Digital Engineering - Mechatronics

These degree courses combine the content of a traditional engineering degree course with the content of computer science in equal parts. In order to provide a solid education in both fields, the courses have a standard duration of 7 semesters, one semester longer than typical engineering courses.

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The aim of the degree courses is to integrate engineering and computer science. They combine the essential elements of an engineering degree program with practice-relevant components of computer science, in particular software engineering and machine learning.
Digital Engineering offers demanding degree courses that address the key challenge of future industrial value creation: The integration of classical engineering tasks and software.
The challenge of "software competence" for engineers has now arrived in the press and in everyday life. From electric cars and smart meters to Industry 4.0, a lack of software expertise among engineers is currently the bottleneck to more innovative products and better quality. The share of software in value creation is increasing steadily and rapidly, meaning that this challenge will gradually affect all areas of our lives.
A second dominant driver of innovation is "artificial intelligence", in particular machine learning. In the engineering environment, data-driven models are increasingly being used alongside classic white-box models(first principles models) based on the laws of mechanics, electrical engineering, thermodynamics and fluid dynamics, etc. These so-called black box models are, for example, neural networks and are trained using measurement data (or simulation data). This allows many very complex processes to be described relatively quickly and cheaply. This gives rise to many new important issues in research and practice in terms of robustness, reliability and interpretability, which require both computer science and engineering expertise.
Other important areas of application of machine learning in the modern industrial environment include the automated evaluation of large amounts of data(big data), so-called data mining, image processing and expert systems based on large language models (ChatGPT) and intelligent search (Google, Bing).
The mathematics component is almost identical in the three degree courses:
  • Advanced Mathematics I and II
  • Discrete mathematics
  • Numerical Methods and Advanced Mathematics III
and the computer science component is identical in the 3 degree programs:
  • Digital Technology
  • Algorithms and data structures
  • Object-oriented and functional programming
  • Programming internship
  • Introduction to machine learning

The different weighting of the contents of the three degree programs can be seen in the following table based on the credit points:

Tabelle der Leistungspunkte Studiengänge Digital Engineering
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Profiles of lecturers at the University of Siegen

Find profiles, contact details and further information on the lecturers of your degree program.

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Career prospects

Depending on their specialization (Biomedical Technology or Digital Public Health), graduates of the DBHS degree program find employment opportunities in the pharmaceutical industry, hospitals, insurance companies, healthcare associations, companies in the healthcare industry, in workplace health promotion or public institutions such as health authorities in municipalities.

Internship information

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Formalities

All formalities can be found on the website of the Examination Office. The current version of the internship regulations is relevant for the Bachelor's degree program. The reading version contains the most recently approved internship regulations including the valid amendments.

Further links

Study plan

Module handbooks

Examination regulations

Examination regulations

Link to the faculty

Advice and contact

Study coordination and academic advising

The study coordination team organizes the degree course, ensures the quality of teaching and provides advice on studying and applying. The Student Advisory Service answers individual questions - you can also find a lot of information on the department's website.

Contact

  • NN:
    +49 271 / 740-XXXX

  • NN:
    +49 271 740-XXXX

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    e-mail

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    PB-A XXX

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    Paul-Bonatz-Straße 9-11
    57076 Siegen

Сontact time

Monday:
9:00-15:00
Tuesday:
9:00-15:00
Wednesday:
9:00-15:00
Thursday:
9:00-15:00
Friday:
9:00-15:00

Responsible examination office

The Examinations Office is your point of contact for all questions relating to examinations: from registration and submission to the overview of grades. Here you will also find information on examination regulations, deadlines and final documents.

Contact

  • Nutzer Icon

    Bettina Neite
    Janine Ising

  • +49 271 / 740-4609

  • Briefumschlag Icon

    e-mail

  • Icon Büro

    PB-A 242

  • Icon Kartennadel

    Paul-Bonatz-Straße 9-11
    57076 Siegen

Сontact time

Monday:
9:00-11:00
Tuesday:
9:00-11:00
Wednesday:
9:00-11:00
Thursday:
9:00-11:00

Responsible internship office

The Internship Office will support you with all questions relating to your internship. Here you will receive information on requirements, recognition procedures, deadlines and necessary documents. It also helps with the organization and advises you on suitable internship positions.

Contact

  • Nutzer Icon

    Dr.-Ing. Nicolas Sänger
    Janine Ising

  • +49 271 / 740 - 2570

  • Briefumschlag Icon

    e-mail

  • Icon Büro

    PB A-242/1

  • Icon Kartennadel

    Paul-Bonatz-Straße 9-11
    57076 Siegen

Сontact time

Monday:
7:30-11:00
Tuesday:
7:30-11:00
Wednesday:
7:30-11:00

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Student Council

The Faculty of Science and Technology offers a wide range of Bachelor's and Master's degree courses.

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Created on 28.03.2025 by Thomas Reppel, last modified on 12.05.2025