Artificial Intelligence – Research and Application
Artificial Intelligence (AI) technology transforms and disrupts the way we perform and manage science. New and in particular large-scale AI methods and applications will become an important pillar of research for organisations that have the resources – talent, knowledge, technology, and data – to develop them.
As a cross-domain research area, AI is covered by a wide range of activities in various groups and research domains. The Jülich Supercomputing Centre provides expertise and infrastructure, ranging from the collection of new data for AI model training, the training itself, and the research into novel AI methods to the development of a wide range of AI models, including foundation models.
Expertise in various AI methods at JSC offer very good prerequisites for advancing the development and application of AI in the scientific domains.
Utilizing synergies between researching and developing AI methods and their application for various research domains is a key objective at JSC. Synergies are developed between domains, method development, and technologies.
AI Research in Science and Engineering requires close cooperation of applied informatics, numerical mathematics and AI with computationally and data intensive disciplinary fields such as neuro-, neutron, materials and earth system science, energy research, engineering, physics, chemistry, biology, and humanities. The research strategy is both domain-specific and cross-domain oriented.
AI Infrastructure at Jülich
The JSC aims to create excellent conditions for the use of AI. We achieve this, for example, by providing the necessary computing infrastructure and support to science and industry. Complex AI algorithms can only be trained and used on powerful supercomputers. JSC will soon host JUPITER, Europe's first Exascale supercomputer and one of the world’s fastest AI computers.
The JUPITER AI Factory (JAIF) serves as a one-stop shop for both research and industry, offering simplified access to JUPITER. The focus is on strategic key sectors, including healthcare, energy, climate change, education, media, the public sector and finance.
AI activities at JSC in various groups and research domains
Data collection for AI models
AI and ML for Healthcare
The research group AI and ML for Healthcare aims to develop machine learning-based solutions for clinical support applications.
Earth System Data Exploration
The research group Earth System Data Exploration (ESDE) develops innovative methods and tools for the integration and analysis of complex, heterogeneous, and big datasets related to air pollution, weather and climate.
ATML Data Management and Analytics
The group Data Services and Infrastructure develops and operates generic data services for publication and sharing, as well as community specific data services. We also operate UNICORE and Cloud services integrated in various federated infrastructures.
SDL Astronomy and Astrophysics
The research group AI and ML for Healthcare aims to develop machine learning-based solutions for clinical support applications.
AI methods: machine learning, deep learning and neural networks
Simulation and Data Laboratory Quantum Materials
SDL Electrons and Neutrons
Simulation and Data Lab Neuroscience
The Simulation and Data Lab (SDL) Neuroscience is an interdisciplinary team of scientists and engineers with complementary backgrounds and skills, dedicated to supporting neuroscientists in using High-Performance Computing (HPC), Cloud and data resources for their research.
ATML Data Management and Analytics
The group Data Services and Infrastructure develops and operates generic data services for publication and sharing, as well as community specific data services. We also operate UNICORE and Cloud services integrated in various federated infrastructures.
SDL AI and ML for Remote Sensing
SDL AI and ML for Remote Sensing
The group Data Services and Infrastructure develops and operates generic data services for publication and sharing, as well as community specific data services. We also operate UNICORE and Cloud services integrated in various federated infrastructures.
SDL Fluids & Solids Engineering
SDL Numerical Quantum Field Theory
Numerical studies of strongly interacting/correlated matter.
SDL Applied Machine Learning
AI-related cross-domain research
ATML Visualization & Interactive HPC
ATML Advanced Time Integrators
This ATML focusses primarily on the design, analysis, implementation and optimization of advanced time integrators (ATI) and space-time multilevel methods for extreme scale HPC systems.
ATML Data Management and Analytics
The group Data Services and Infrastructure develops and operates generic data services for publication and sharing, as well as community specific data services. We also operate UNICORE and Cloud services integrated in various federated infrastructures.
AI models: foundation, multimodal and large language models
SDL Applied Machine Learning
Earth System Data Exploration
The research group Earth System Data Exploration (ESDE) develops innovative methods and tools for the integration and analysis of complex, heterogeneous, and big datasets related to air pollution, weather and climate.
SDL AI and ML for Remote Sensing
SDL AI and ML for Remote Sensing
AI support and teaching
SDL Applied Machine Learning
ATML Application Optimisation and User Service Tools
