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Field
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characteristics of the case study areas. Geographical Information Systems (GIS) will be used to integrate and analyse these datasets, and a range of econometric and statistical modelling methods will be used
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this ecosystem service. The student will map pedestrian networks using GIS and combine this with existing vegetation data. Field surveys will be conducted to validate the spatial data by measuring shade and
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, nanofabrication, and computational electromagnetism. Strong coding (Python /MATLAB) and experimental aptitude is desirable.
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and 2). These measurements will then be incorporated into a GIS and compared to historical records of the position of channel networks prior to reclamation, such as aerial photography, to validate
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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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, environmental data science, or a closely related STEM discipline Demonstrated expertise in urban spatial data analytics, with proficiency in GIS software (e.g. QGIS, ArcGIS) and geospatial methods Experience in
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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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tools (STATA, R, or Python). Assist in literature reviews and summarising academic research. Contribute to writing research papers and policy reports. Participate in meetings with collaborators and
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languages such as Python for data analysis and simulations. Experience with optical systems, astronomical observations, or satellite tracking would be advantageous, although not compulsory. Strong analytical
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into longitudinal studies and in using functional MRI and scripting-based languages (e.g. Matlab, R, Python). They must also have experience of conducting research with human participants and of performing highly