We want to show you that carrying out experiments, doing research, and constructing buildings isn’t just for boys! Besides experiencing our university from the inside, you will have the opportunity to gain fascinating insights into the work of women scientists and engineers, and you will have the rare chance to become active yourself.
Here’s how you find your place at Girls’ Day
1. Leave of absence from school
Talk with your parents or with your teacher and ask them if you could participate in the Girls’ Day. Because, of course, the prerequisite is that you are exempt from school on that day by application.
2. Find a workshop
In 2023, we offer a variety of Girls' Day events [de].
In the overview list you can filter by grade to find the right workshops for you.
3. Register
After you have found the right place at Girls’ Day, you can sign up via the link on the respective event page. There you have to register with your personal data, and then you can sign up for the event.
After successful registration, you will receive a confirmation link to your email address within a few minutes. You are only actually registered if you click on this confirmation link within 24 hours! Otherwise, your registration will be deleted and the place will be made available again.
You will receive another email with the access data for online events or, in the case of a face-to-face event, with precise information about the meeting point and venue. Please make sure that there is enough space in your mailbox for the mail to be received. If you do not receive this mail, please let us know in time, so that we can send it again.
Software and data expert Prof. Bernhard Mitschang brings together computer science and production. Their almost complete networking and comprehensive digital data production and provision can be found in the digital real-time capable factories, the so-called advanced manufacturing, in the entire field of Industry 4.0 and also in the cyber-physical IT systems. Trending terms in this area are Big Data, Data Mining, Machine Learning and also Data Science. Mitschang and his team have adapted their research to best answer the questions posed by Big Data and data analysis in the respective industrial application context.