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data (e.g. instrumental, laboratory, environmental, numerical and categorical data, text, geospatial data or time series); c) Experience in Python programming and in data analysis and machine learning
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open-source materials, remote sensing and geospatial data, and survivor and witness testimony. The Centre's methodological approach is interdisciplinary, and the successful candidate will benefit from
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Change Adaptation (CCA) simulations and activities in urban environments. The PhD project should leverage multi-scale geospatial data (remote sensing/aerial imagery, point clouds, maps, etc.) and GeoAI
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for admission. The project would suit a candidate with a background in surveying/geodesy, geomatics, remote sensing, geospatial science, civil/environmental engineering, hydrology, Earth observation
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by a more experienced theoretical postdoc. In the second phase of the project, work will move towards current-driven dynamics of the nanosized textures, the exploration of topological excitations, and
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combines microfluidics, bubble physics, and ultrasound signal processing to bring nanobubble imaging closer to clinical use. You will collaborate closely with a fellow PhD candidate, a postdoc, and a
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Python. You will work in a newly formed team of two postdocs and a PhD student, led by the PI (Ekaterina Ilin), and collaborate closely with both postdocs, who will be working primarily on a large optical
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environmental challenges? Join the Department of Physical Geography at Utrecht University as a PhD candidate and help shape the next generation of geospatial modelling. Your job Predicting ecosystem dynamics
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the project team with a Postdoc and the Project Leader. The daily supervisor of the PhD-project is Pepijn Corduwener, the Project Leader; co-promotors are Professor Liesbeth van de Grift (International History
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. Experience working with geospatial data and spatial analysis, or the ability to learn. Experience analysing whole genome libraries, including quality control, sequence alignment, and calculating population