Sort by
Refine Your Search
-
conducting laboratory work Experience in planning and conducting field work Insight into and experience with applied statistics, microbial ecology, soil health indicators and interdisciplinary collaboration
-
work Insight into and experience with applied statistics, soil mapping, soil health indicators and interdisciplinary collaboration Who we are At the Department of Agroecology, our main goal is to
-
frameworks. Strong knowledge of probabilities and statistics. Ability to work in a UNIX environment. Demonstrated the ability to publish in the international peer-reviewed research literature Proven ability
-
environment with 400 employees and 10 research sections spanning the scientific disciplines of mathematics, statistics, computer science, and engineering. We offer education ranging from bachelor's degrees
-
, scipy, scikit-learn, pytorch, pytorch geometric, etc.). Proficiency in statistics and graph machine learning, including the ability to build and deploy models, and evaluate their performance. Software
-
of statistical analyses and modelling. Experience in handling and analyzing large datasets. Experience in employing high performance and cloud computing services. Knowledge in GIS. Knowledge on obtaining
-
of statistical analyses and modelling. Experience in handling and analyzing large datasets. Experience in employing high performance and cloud computing services. Knowledge in GIS. Knowledge on obtaining
-
on developing machine-learning-based or statistical emulators to approximate key outputs of complex Earth System Models, with the aim of enabling efficient uncertainty quantification, sensitivity analysis, and
-
a good knowledge of statistical mechanics, good English communication skills and experience with all-atom or coarse-grained molecular simulations. The candidate should be comfortable with programming
-
at the Dynamical Systems Section is very wide ranging. From foundational research in work on statistical forecasting, modeling of spatial and temporal processes and time series analysis to applied research in wind