Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more efficient, intelligent, and impactful. You will integrate field
-
, water quality, and data science; collects and harmonizes data from a variety of sources; develops analyses and reproducible workflows for hydrologic and biogeochemical data; interprets results and
-
: Using biogeochemical evolutionary models to simulate lifeless and inhabited worlds, and Developing disequilibrium-, redox-, and information-based metrics to understand and quantify the influence of life
-
modelling of nature-based solution to enhance the resilience of Mediterranean agro-silvo-pastoral ecosystems and landscapes, with reference GA nº101156076, taking place at the Forest Research Centre (CEF) of
-
Unit, Marine Microbial Ecology Research Unit, Marine Biogeochemical Dynamics Research Unit, Marine-Earth System Analytics Unit, Marine Ecosystem Modeling Research Unit *Successful candidates will be
-
well as a strong interest in climate science and biogeochemical cycling. Previous experience applying Bayesian inference, data assimilation, inverse modeling, and/or probabilistic machine learning
-
measurements, behavior, and modeling; its connection with the biogeochemical cycling of C, N, and P, and fundamental biological and chemical processes controlling organic carbon sequestration in the soil
-
to biogeochemical cycing of essential elements in the soil system. We also welcome potential candidates who are eager to develop their own research projects within these areas. We value collaborative and
-
environmental conditions and the analysis and modelling of the consequences of interventions in biogeochemical cycles. The social science methodology is included in the context of human ecology, political ecology
-
microphysics, severe storms, and mesoscale meteorology; data assimilation, machine learning, and causal discovery; education and human resources; global biogeochemical cycles and ecosystems; and radiation and