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of objects relevant to AWE’s mission. Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related
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Application’. Use ‘Course Search’ to identify your programme of study: · search for the ‘Course Title’ using the programme code:8209F · Select ‘PhD Water Infrastructure & Resilience (WIRe)' as the
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Health threats often affect different population groups in unequal ways, exacerbating existing health disparities. When health threats occur, however, community-based organisations play a crucial role. Positioned at the grassroots level and operating from a foundation of trust, these...
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Supervisors: Dr Katherine Finlay, Psychology (Lead) Collaboration Partners: Dr Alexandra Oti, Unravel Health Dr Chanais Matthias, Manchester Metropolitan University Project Overview: Hormone-driven conditions affect billions of women globally, impacting everything from cardiovascular to mental...
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Project advert Reckless Sleepers is an internationally-renowned performance company, situated between the Northwest of England and East Flanders, Belgium. Situated in the fields of scored performance, performer training and performing archives, this PhD will examine how engagement with an...
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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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academic requirements for your preferred programme, in addition to those specified by the Commonwealth Scholarship Commission. Nationality restrictions This funding is available to students from: Bangladesh
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the PhD studies in the Faculty of Humanities in the academic session 2022-23. Funding provider Engineering and Physical Sciences Research Council Level(s) of study This funding is available to students
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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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home to 200 doctoral candidates in Physics at the University of Vienna who work at the forefront of science and receive training, mentoring and support to become independent researchers and to connect