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, postdoctoral researchers, and technicians is expected.
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, the project will enable the evaluation and optimization of resilience strate-gies. The framework will be validated through pilot studies, ensuring its applicability to real-world industrial chal-lenges
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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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archaeological finds. Conducting geospatial analyses in GIS, including work with LiDAR data, aerial imagery, and other remote sensing data. Developing a webGIS platform to host field-collected data, legacy
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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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(including the Dutch Center for RNA Therapeutics and Charles River Laboratories). Informal yet close collaboration with fellow PhD candidates, postdoctoral researchers, and technicians is expected. Where
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investigator of the project and two postdoctoral researchers working on the other CEE countries. Your daily job will involve theoretical and methodological preparations, independent ethnographic fieldwork in
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experiment at the LHC. The project will be conducted in close collaboration with Dr Flavia de Almeida Dias and a postdoctoral researcher in experimental particle physics. Your appointment will be for four
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Hungary or Czechia and Poland or Ukraine and Georgia). You will closely collaborate with Johana Kotišová as the principal investigator of the project and two postdoctoral researchers working on the other