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Field
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elaborations called awns that have diversified in form and function in the grasses (see Schrager-Lavelle et al, 2017; Patterson et al, 2023, 2024). Both floral sexuality and awns can be important in crop
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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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to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging through health, retail, mobility, energy and communications. Using GI infections as a case study
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infectious diseases such as gastrointestinal (GI) infections, respiratory infections and sore throats. Using GI infections as a case study, the project will compare trends in OTC medication sales to other
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science”, led by Dr Susan Hegarty. The PhD position will be focused on developing the citizen science hydromorphology framework, and is open to candidates with strong GIS skills and an academic background
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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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changes occur in earthworm signals. As part of the project, soil vibration data will be collected from the Long-Term Experiment ‘Park Grass’ at Rothamsted Research. This is the only experiment in the world
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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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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