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Field
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cracking resistance as compared to GI galvanized steel. Furthermore, it is unclear at this moment how these types of coatings will perform in application to the green steel. Therefore, this project is aimed
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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
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, 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
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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
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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
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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
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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
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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
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., 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
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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