Event Program 2022

In 2022, the ErUM Data Hub, in collaboration with the DIG-UM Topic Board Knowledge Distribution, will host interesting events around the topic of Deep Learning. The workshops and schools are aimed at participants from all ErUM communities and are held at different locations in Germany. 

The 2022 annual program includes two Deep Learning Train-the-Trainer workshops in March and June, a Deep Learning Beginner School in August, an Expert Workshop in September, and an Advanced Deep Learning School in October. 

Registration and Announcement

Registration for the workshops and schools will be done through Indico Events. The links to the events will be announced here. We look forward to active participation from all ErUM communities. Feel free to distribute the event poster. 

Upcoming ErUM-Data-Hub Events

Active Training Course

Advanced Deep Learning

Vom 28.11.22 bis zum 01.12.22 veranstalten der ErUM-Data-Hub und DIG-UM die zweite Deep Learning Schule. Im Landhaus Nordhelle in Meinerzhagen wird über 4 Tage intensiver Unterricht zu den Themen Graph Neural Networks, GANs, Autoencoders und Normalizing Flows gehalten. Vorkenntnisse über neuronale Netze sind erforderlich. Die Teilnahme an der ersten Deep Learning Schule ist jedoch keine Voraussetzung.

Register now

Der Workshop findet als Präsenzveranstaltung in Meinerzhagen statt und ist auf 40 Teilnehmer:innen begrenzt. Die Teilnahmegebühr beinhaltet Unterkunft und volle Verpflegung. Anmeldungen sind voraussichtlich ab Ende August 2022 möglich.

More ErUM-Events

Find more exciting networking and education opportunities within ErUM Communities here.

5 - 7 September 2022

DAPHNE & ErUM-Data Microsymposia at SNI2022

DAPHNE4NFDI and ErUM-Data will be present in one of the Microsymposia (Digitalization) and also topics like Artificial Intelligence for Large-scale Facilities will be discussed within the three day SNI2022 conference in Berlin.

12 - 16 September 2022

PaNOSC Summer School

PhD Students and Postdoc researchers that want to increase their knowledge about the latest data-driven tools and methods to leverage large scale scientific research infrastructures are invited to join the PaNOSC Summer School on “Material Science at European Large-Scale Infrastructures using Open and FAIR Data” at ELI-ALPS in Szeged, Hungary.

Past Events

Past Events

Deep Learning Workshop


On March 30 and 31, 2022, the first ErUM Data Hub Workshop took place in Aachen, Germany. The Deep Learning Train-the-Trainer Workshop included 4 lectures on the topics Deep Learning Basics, Convolutional Neural Networks, Recurrent Neural Networks and Introspection Neural Networks and aimed at training lecturers for future teaching activities and providing material for lectures on Deep Learning.

Deep Learning Workshop

Train-the-Trainer 2

Advanced Concepts

From June 09 to June 10, 2022, the ErUM Data Hub and DIG-UM hosted the second Train-the-Trainer Deep-Learning Workshop. The workshop was aimed at scientists from all ErUM communities who have prior knowledge in the field of neural networks. The participants showed a high willingness to give Deep-Learning lectures at schools and workshops in the future. 

Deep Learning School I

Basic Concepts

Basic Concepts

In August 2022, ErUM-Data-Hub and DIG-UM hosted the first Deep Learning School at Landhaus Nordhelle in Meinerzhagen. In a beautiful ambience, intensive classes on Neural Network Building Blocks, Mastering Model Building, Convolutional Neural Networks, Recurrent Neural Networks and Introspection of Neural Networks were held over 4 days. The school was aimed at beginners from all ErUM communities who have a basic knowledge of physics. 

Conceptual Advances in Deep Learning for ErUM Research

Conceptual Advances in Deep Learning for ErUM Research

Expert Workshop

Expert Workshop

From 12.09.22 to 16.09.22 the ErUM-Data-Hub and DIG-UM organized a workshop on Conceptual Advances in Deep Learning. The workshop took place at the Hotel zur Post in Wiehl and was aimed at advanced users. The program included the following topics:

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