Sort by
Refine Your Search
-
, you will develop innovative small area estimation methods to produce high-quality composite SDG indicators, combining survey, census, and non-traditional data sources such as web and satellite data
-
how Europe measures economic well-being at the local level. In this project, you will develop innovative small area estimation methods to produce high-quality composite SDG indicators, combining survey
-
) are among the protection layers for our groundwater systems. They seal and compartmentalise aquifers, protecting drinking-water reservoirs from contamination, separating different groundwater compositions
-
linking these subjective perceptions to behavioural and contextual indicators, such as voting patterns, neighbourhood composition and participation in local initiatives, we can identify where misperceptions
-
implementation, including demographic composition, minority stakeholder influence, HR and diversity roles, and accountability mechanisms (Ellemers & van der Toorn, in press). DEI policies are also politically
-
environment, including tasks such as calculating sample compositions. A quantitative mindset with the ability to analyse data, make predictions, and perform back-of-the-envelope calculations. Mindset and
-
lead to shifts in microbial species composition and ultimately reducing soil’s water-holding capacity. The spatial distributions of such soil communities, the changes in (functional) diversity
-
deteriorating microbial (soil) communities that are also affected by these stress factors and this may lead to shifts in microbial species composition and ultimately reducing soil’s water-holding capacity
-
state-of-the-art magnetic imaging with advanced electron microscopy techniques. You will generate high-quality experimental datasets that form the basis for data-driven micromagnetic modelling developed
-
programming techniques (e.g., techniques for differentiating effectful programs such as gradient estimation of probabilistic programs, implicit function differentiation, compositional Bayesian inference