Sort by
Refine Your Search
-
on beaches. During the project, you will be involved in: setting up hydrodynamic coastal flow fields using SWAN, SWASH, SCHISM or a comparable model; writing python code to advect virtual macroplastic items in
-
). Quantitative Skills: An affinity with quantitative methods, mathematical modelling, simulation, or data analysis. Experience with tools such as R or Python for modelling is an advantage. Resilience and
-
quantitative data analysis using R and/or Python; experience with statistical modelling and the analysis of complex biological data; a strong interest in exposomics, multi-omics integration, and brain–body
-
science research, including familiarity with methods and tools (e.g., statistical software such as R and Python) common in social science; A strong track record in collaborative research, including
-
hydrodynamic coastal flow fields using SWAN, SWASH, SCHISM or a comparable model; writing python code to advect virtual macroplastic items in these flow fields using the Parcels-code.org framework; exploring
-
excellent communication skills; have experience and knowledge in modeling and optimization, preferably with Python; have experience and knowledge of techno-economic assessment of energy projects; be able
-
and transport in porous media; Strong analytical skills and ability to integrate experimental observations with computational approaches; Proficiency in at least one programming language (Python, MATLAB
-
and written. Further expertise that would be valuable: Python software development; Natural Language Processing. Above all, you are a quick learner, proactive and eager to make things work. Our offer
-
quantitative methodological skills, for instance knowledge of (spatial) data analysis, hydrological modelling, AI-based methods Experience with programming languages (e.g. Python) Motivation to cooperate in a
-
, Introduction to Python, making figures using GGplot2 and basic machine learning. These courses are offered to PhD candidates through the PhD Course Centre of the Graduate School of Life Sciences . In