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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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neuroimaging and mc-tCS simulation approaches based on realistic head volume conductor models using modern finite element methods as well as sensitivity analysis. The new methods will be applied in close
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ability to quantify and model these processes remains limited, contributing to uncertainties in global carbon sink estimates. You will analyze data and samples from past and upcoming expeditions to evaluate
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, extension is sought) Contract:TV-L Your tasks Molecular laboratory work with 2D and 3D cell culture models Experimental design, data analysis and interpretation Publishing research findings in peer-reviewed
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and physiological function of specific transport proteins in heterologous expression systems in crops and (trans-genic) model plants. • A unique set of Arabidopsis and barley transporter “mutants
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of fluid dynamic modeling and the analysis of thermomechanical stresses, you will accompany the entire development process – from the optimization of electrochemical performance to the elaboration
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
), statistical analysis, modelling, and mapping Highly motivated and eager to work in an interdisciplinary marine research context Excellent communication and teamwork skills, with the ability to collaborate
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Postdoc in "Navigating uncertainty: Planning marine protected areas in a changing Southern Ocean"...
statistics and the ability to apply quantitative analysis to ecological data A strong background in programming (preferably in R), including data manipulation, statistical analysis, and spatial modelling and
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Excellent skills in statistical modelling, preferably using R Proven track record of publishing in international peer-reviewed journals as first author Willingness to conduct fieldwork and participate in
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on skills and interest): Build “incentive-preserving prediction models” for variables with positive global externalities, based on country characteristics (GDP, population density…) Develop procedures