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an unprecedented computing and storage infrastructure. Processing these enormous amounts of data in a future data center, however, consumes significant resources. The fundamental challenge is: How do we build and
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link these to mesoscale activity representations collaborate on project-related scientific software development and data management processes for reproducible science contribute to the HDS-LEE graduate
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evaluation strategies. In close collaboration with chemists, engineers and data scientists, a platform is being developed that combines materials development, process optimisation and machine learning
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sustainable operation of future energy networks by combining our knowledge of energy systems with cutting-edge developments in machine learning, generative AI, and digital infrastructures. Your Job
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) is one of the world-leading groups in the field of computer simulations of active, soft and living matter systems, such as cells, bacteria, tissues, and active synthetic colloids. Our aim is to provide
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tools that enable the energy-optimal, cost-efficient and safe design and operation of future energy systems. Your Job This PhD position focuses on scenario development, as well as the modelling
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are an advantage Please feel free to apply even if you do not yet meet all the required skills and qualifications. We may be able to provide training for these during the onboarding process. Our Benefits for You We
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companies. The project has partners from eight different EU countries. All 15 Ph.D. projects are within the overall theme of neuromorphic computing and analog signal processing, targeting applications in
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is successfully filled. Index number: 2026D-0644 Application Process FAQ Contact form Career portal Forschungszentrum Jülich GmbH Legal Notice This research center is part of the Helmholtz Association
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of trustworthy, scalable, and interoperable AI solutions for the operation and management of modern electricity networks. We are currently seeking a Ph.D. student to research the following topics: Development