Helmholtz Imaging Project - Deep-learning assisted fast in situ 4D electron microscope imaging (FAST-EMI)

Together with Prof. Dr. Christoph Kirchlechner and Dr. Subin Lee from Karlsruhe Institute of Technology, our vision is to create tailored imaging approaches that unlock the full potential of in situ 4D-STEM-in-SEM. Therefore, we are developing a model to couple a novel 4D-STEM-in-SEM measurement method with deep learning algorithms in order to improve the temporal resolution of the measurements and to significantly shorten the measurement duration.

Helmholtz Metadata Collaboration
The HMC Hub Information works towards optimized metadata that allows researchers to connect in cross- and multidisciplinary collaborations. We help to bridge the gap between discipline specific problems by endorsing, adjusting and developing cross-disciplinary solutions for the creation, curation and management of scientific metadata.
The Working Package FAIR Data Commons: Technologies and Processes facilitates compliance with the FAIR principles for research data coming from all scientific fields covered by the Helmholtz Association and beyond. It will foster uniform access to metadata by providing standardized interfaces, which are in line with recommendations and standards adopted by global research data initiatives, e.g. the Research Data Alliance (RDA). These interfaces will be accomplished by easy-to-use tools, generally applicable processes, and best practices in order to support scientists in their daily work. In addition, training and consultancy services will be offered in order to make the transition to FAIR research data even easier.

Electron Microscopy Data Science Lab
This interdisciplinary simulation and data science lab, co-hosted by the Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons (ER-C) and lead by the IAS-9, is initiated to create added value by combining competencies and know-how in data science, computational materials science as well as research data management, all with a focus on the field of electron microscopy.
Helmholtz School for Data Science in Life, Earth, and Energy

HDS-LEE is an international, English-speaking graduate school and a cooperation between RWTH Aachen University, the University of Cologne, the German Aerospace Center (DLR), the Max-Planck-Institut für Eisenforschung, and Forschungszentrum Jülich. HDS-LEE is part of the newly founded JARA Center for Simulation and Data Sciences (JARA-CSD), which will be created as a unique, internationally visible competence center for computer- and data-infrastructures, user support as well as methodological and disciplinary research in the fields of simulation, data analysis and HPC technologies.