Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Swedish University of Agricultural Sciences
- Tallinn University of Technology
- University of Basel
- KU LEUVEN
- Leiden University
- Nantes Université
- Nature Careers
- Technical University of Munich
- UNIVERSIDAD EUROPEA
- UNIVERSITY OF VIENNA
- University of Sheffield
- University of Vienna
- Universität Wien
- Vrije Universiteit Amsterdam (VU)
- 4 more »
- « less
-
Field
-
data (nationwide LiDAR coverage at 50 cm resolution). The candidate will perform quantitative morphometric analyses of landscapes and river networks near suspected active faults using GIS tools, Python
-
programming (R or Python). Advantageous: geostatistics, digital soil mapping, remote sensing, GIS, big data or cloud tools. Proactive working style, strong communication skills, and excellent English. Relevant
-
of guaranteeing thermal comfort throughout all seasons. The project will be developed by integrating parametric urban design with microclimate simulations and measurements, GIS and Digital Twin technologies, and
-
science, or a related field; strong experience with GIS and spatial data analysis; experience with Python, or a strong willingness to further develop programming skills; an interest in methodological and
-
biochemical models, data assimilation, spatial analysis and GIS approaches. • Programing skills (e.g. R or Python) for data manipulation and visualisation, and to perform statistical analysis (e.g. mixed models
-
of the department and within the consortium. Where to apply Website https://emer.fa.em3.oraclecloud.com:443/hcmUI/CandidateExperience/es/job/7865/s… Requirements Research FieldBiological sciencesEducation LevelMaster
-
Health, Data Science, Remote Sensing, Geomatics or a closely related discipline•Strong analytical and programming skills (e.g. Python or similar)•Experience in at least two of the following areas
-
, generating evidence to support long-term climate adaptation and investment planning. Students will build a comprehensive set of high-value technical and professional skills, including: • Geospatial and GIS
-
(preferably in R, Python, GIS) • Competences in quantitative research methods - ideally knowledge of several of the following aspects of quantitative data analysis: analysis of large/longitudinal datasets
-
-authored peer reviewed papers) • Well-developed statistical software skills (preferably in R, Python, GIS) • Competences in quantitative research methods – ideally knowledge of several of the following