60 gis-python-"NTNU---Norwegian-University-of-Science-and-Technology" positions in Switzerland
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collaboration among scientists, IT professionals, and other stakeholders involved in the research process. To achieve its goals, the R-IT group invites applications for a R/Python scientific support role
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yourself further with scientific software packages (e.g., scripting languages, GIS software, MATLAB, Python, R, Stata, etc.). Enjoyment of scientific work. Ability to work in a team, have problem-solving
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. Candidates should be able and willing to conduct fieldwork in the Swiss Alps, have experience and knowledge in plant species identification, and hold a valid driver's license. Experience in GIS, project
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, Environmental sciences, or a closely related field. Proficiency in programming, particularly in Python, is essential. Knowledge of GIS (QGIS or ArcGIS). Experience working with spatial data, shapefiles, raster
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responsibility for our unique GPU-accelerated 3D FDTD software suite and extending its capabilities Modelling the effects of atmospheric turbulence fields Software development (3D modelling and coding in Python, C
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experience with computer modelling, (e.g. agent-based modelling), as well as good grasp of machine learning, forecasting techniques, scenario planning, optimisation, Python and GIS. Good knowledge of English
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ideal for students with strong technical and organizational skills, particularly those with experience in LaTeX and Python programming. Some background in economics is a plus but not strictly required
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to the fields of architecture and engineering. We have developed an open-source python library called AIXD ( https://aixd.ethz.ch/docs/stable/ ) for ML-assisted forward and inverse design. In the framework
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reports Profile MSc or PhD in Earth Sciences or closely related field Proven advanced expertise in 3D geological modelling Experience in managing diverse geological datasets (e.g., GIS data, 3D meshes
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observation data, including drone-based data (RGB, LiDAR, hyperspectral). Strong skills in geospatial and statistical analysis (e.g., GIS, remote sensing software, R/Python). Experience in data preprocessing