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to model and analyse the intrinsic complexities of these systems. This research direction requires advancements in modern probabilistic tools, including spatial random graphs, random walks, and Markov chains
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xenograft (PDX) models. To this end, the candidate will have direct access to cutting-edge mass spectrometry and advanced bioinformatics infrastructure. The project is part of the collaborative research
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identify the necessary solutions. The findings should also remain valid under different climate change scenarios. With its global state-of-the-art energy system model, ICE-2 at Forschungszentrum Jülich
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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Great interest in pre-clinical in vivo models Ideally initial experience with Bioinformatics experience, especially in R What we offer Goal-oriented, individual training and development opportunities
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histological validation within murine cancer models. We offer an association with the Collaborative Research Centre 1450 “Insight – Multiscale imaging of organ-specific inflammation” graduate school
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support the development of a European energy system model by benchmarking future technologies and optimizing their representation within the FINE optimization modelling framework ( https://github.com/FZJ
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cellular biology, the project will investigate signal transduction mechanisms at the protein and membrane level. Experimental systems will include 2D cell culture, organoid models, and advanced biophysical
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of Munich, Cologne and Hanover as well as the German Weather Service in Offenbach and Lindenberg. The partners combine leading expertise in modeling and observing clouds and their radiative properties with
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sites will not be located directly at the source of emissions, which will require transport infrastructure. As part of this work, you will model spatially resolved transformation paths for the energy