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Field
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analysis methods. You will gain expertise in integrating experimental total scattering and high-resolution imaging data with artificial intelligence and atomistic simulation tools to overcome current
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-motivated in advancing science. Their active involvement in this project will contribute to their career development, such as increasing their competitiveness in PhD scholarship applications. The successful
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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives
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@bristol.ac.uk ) 4th Supervisor: Professor Jenni Barclay (J.barclay@bristol.ac.uk ) Applications are invited for a fully funded three years PhD studentship. The studentship will start on 1st January 2026
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hepatitis C virus (HCV)) among migrants to high-income countries through systematic review and, if appropriate, meta-analysis; • building on previous work linking administrative immigration data with
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science, data analysis, socio-economically-driven decision-making, and collaborative research, highly sought-after skills. Number Of Awards: One Start Date: Autumn 2025 Award Duration: 4 years Application
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-scale job ads datasets, spatial datasets, patents). Conduct data analysis using econometric and statistical tools. Excellent knowledge of R is expected. Good knowledge of Python, experience with modern
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weather events and improve household resilience. Key responsibilities include: Data cleaning, management, and econometric analysis Supporting fieldwork design and survey development Preparing research
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breast cancer in animal models (4). In this PhD project, we will investigate: The effect of combined treatment with ITCs and a selected anti-cancer drug (sorafenib or triptolide) on breast cancer will be
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. The successful candidate will be expected to: Conduct PhD research Contribute to the analysis and reporting into issues pertaining to air power and related issues as a member of the FASI team. Assist in