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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
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and family-friendly working time model and the possibility of mobile working (up to 50% of working time) VBL Ost company pension scheme for public sector employees, as well as a collectively agreed
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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
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of heart disease Your studies will take advantage of in vitro and in vivo pre-clinical models, including hiPSC-derived systems The postdoctoral project will combine experimental (wet-lab) and computational
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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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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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of in vitro and in vivo pre-clinical models, including hiPSC-derived systems The postdoctoral project will combine experimental (wet-lab) and computational (dry lab) approaches Be part of Geman Center
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)confinement in string-net models - Quantum field theory, lattice QCD To apply, please send your application via email with the title “PostDoc application” or “PhD application” to application@zachegroup.com
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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