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Degree Dr phil / doctorat en histoire Course location Heidelberg In cooperation with École des hautes études en sciences sociales in Paris (EHESS) Teaching language German French Languages
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genomics, virtual cell models Graph-based neural networks, optimal transport Biomedical imaging, deep learning, virtual reality, AI-driven image analysis Agentic systems, large language models Generative AI
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challenges facing science, society and industry. With its ultramodern research infrastructure, its interdisciplinary research platforms and its international networks, DESY offers a highly attractive working
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institution of all faculties, we support our doctoral and postdoctoral researchers in becoming future leaders in science, business, and society! We also contribute to the university’s network to support junior
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most research-intensive regions. We cooperate closely with the more than 20 internationally renowned research institutions in our vicinity and our network extends to our partner universities in Germany
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sciences (incl. economics), social-ecological modelling, environmental psychology, or related field; Experience in SES modelling, e.g., in qualitative network modelling, participatory modelling, and/or
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PostDoc in "Geopolitical dilemmas for management: transfer of governance for the Southern Ocean" ...
biological effects, including changes in primary production, community composition, and poleward shifts of species. Species that are endemic to the high southern latitudes and specially adapted to cold
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
biological effects, including changes in primary production, community composition, and poleward shifts of species. Species that are endemic to the high southern latitudes and specially adapted to cold
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production, community composition, and poleward shifts of species. Species that are endemic to the high southern latitudes and specially adapted to cold conditions are particularly vulnerable, as their
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The Network Analysis and Modelling group investigates how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. Using machine learning and network