Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Swedish University of Agricultural Sciences
- ;
- University of Groningen
- NTNU - Norwegian University of Science and Technology
- ; Durham University
- ; Swansea University
- ; University of Birmingham
- ; University of Nottingham
- ; University of Southampton
- Curtin University
- Delft University of Technology
- Ghent University
- Leibniz
- Monash University
- Nature Careers
- Norwegian University of Life Sciences (NMBU)
- Sveriges lantbruksuniversitet
- Technical University of Munich
- University of Basel
- University of Göttingen •
- University of Münster •
- University of Nottingham
- Utrecht University
- 13 more »
- « less
-
Field
-
experience with knowledge graph standards (e.g., RDF, OWL, SHACL); familiarity with GIS, geodata infrastructures and geo-analytical workflows some experience with AI and machine learning methods to label texts
-
, energy-related datasets. Proficiency in Python, MATLAB, and/or Julia for modeling, simulation, and data analysis. Familiarity with GIS tools (e.g. QGIS), time-series databases (e.g. InfluxDB), and version
-
degree (2.1 +/MSc) in mechanical / civil / environmental engineering, physics or a related quantitative field; strong computing skills (Python/MATLAB/GIS); interest in transport or urban futures. Position
-
generation of experts in ingestible medical technologies. These orally delivered, minimally invasive devices are designed to traverse the gastrointestinal (GI) tract, enabling diagnostics, therapy, sampling
-
programme No Description/content The Graduate School for Geoinformatics (GSGI) provides a structured doctoral education in the interdisciplinary field of geoinformatics. GI (geoinformation) is a powerful
-
as Physical Geography, Geology, or Engineering Geology, with a numerical background in earth surface processes. Field experience and skills in GIS and programming skills are necessary. The scholarship
-
training in field work techniques, ecological modelling and GIS will be provided by an interdisciplinary supervisor team. Funding duration – 4 years Funding Comment This scholarship covers the full cost
-
., health and climate/environmental data) and could include a range of data science methods, such as utilising geographical information systems (GIS), statistical analysis, machine learning, deep learning
-
topographic indices as environmental variables for mapping, and satellite data for weather. The doctoral student will be part of a broad research group with expertise in GIS, AI, soil science, forest ecology
-
for policy, practice and advocacy. The mixed-methods project will use a combination of participatory approaches including but not limited to GIS mapping, stakeholder analysis, network and systems mapping