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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
Area of research: Scientific / postdoctoral posts Job description: PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate change" (f/d/m/x) Background
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strong quantitative skills and demonstrated experience in applied econometric analysis, large-scale data integration, and global or regional economic modeling, as well as an interest in climate risk, soil
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-based, and climate-related) and uses innovative qualitative and participatory methods to study how care, strategy, and collective action interact in times of societal crisis. You will join a vibrant
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approaches applied to different science domains, such as chemistry, materials, physics, imaging, drug discovery, climate/weather forecast, etc. Knowledge of implicit deep learning models (NERF, neural
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Challenge: Increasing the number of trees in cities is a viable approach to adapt to the changing climate
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attributes are encouraged to apply: Background in large-scale numerical modeling (regional planning, ecological, hydrologic climatic, or wildfire modeling). Experience with scientific software development in C
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. Applicants must have experience in the handling and organization of large data sets. Familiarity with analysis of panel or longitudinal data and working with multilevel models is valued. Additional skills with
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associate will lead collaborative efforts in advancing research focusing on the intersection of infrastructure, climate, and human health. Examples of current active projects include: Developing optimization
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building materials using polyphasic detection and identification approaches. Characterization of biobased building materials with respect to their moisture sorption isotherms. Modelling the correlation
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application of cumulative impact assessment model using food webs, which is intended to assess impact of multi-stressors on trophic and non-trophic interactions networks. The modelling will be primarily based