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motion and the viewing perspective of the observer (Nikolaidis et al, 2016). This project will develop continuous models of action legibility using these sources of information from data collected in a
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This self-funded PhD opportunity focuses on assured multi-domain positioning, navigation, and timing (PNT), integrating data from space-based, terrestrial and platform-based sources of navigation
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with a surface. This project will involve using and further developing both the experimental and data analysis methods that are currently used within the research team. The student will learn how to use
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myriad of new techniques and much sought-after skills demanded by industry, including the following: Design of experiments, data harvesting/analysis and interpretation of results to derive insight
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of synthetic load profiles for domestic heat demand delivered via ASHPs and heat networks. Objectives: • To complete an evaluation of existing heat demand, based on available data sets; • To analyse
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Supervisor: Professor Richard Gilbertson and Dr Giulia Biffi For further information about the research group, please visit biffilab.wordpress.com . Project details Cancer-associated fibroblasts
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Research Office Location: Newport, Shropshire TF10 8NB Post Type: Full Time Contract Type: Fixed Term - 36 Months Closing Date: 23.59 hours BST on Sunday 19 July 2026 Reference: PHD-SELF-OCT-2026
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for a year (Oct 2025 - Oct 2026). Timings can be flexible providing key deadlines are met and important meetings are attended. How to apply For further information please contact Birgitta Gatersleben
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with a background in cognitive psychology, data science or computer science and a willingness to develop skills in computational models of cognitive processes, statistical methods, and programming (R
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-on experience with real-world SCADA data, industry collaboration with RES Group, and training in high-fidelity simulation environments (OpenFAST, Digital Twin technology). This opportunity is ideal for those