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15th August 2025 Languages English English English The Department of Materials Science and Engineering has a vacancy for a PhD Candidate in Development of Aluminium Batteries for Stationary Energy
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localised economic gains. These contrasting findings highlight the current uncertainty surrounding the specific impacts of AMOC weakening on human societies. In this PhD project, you will use models and data
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qualifications Documented experience with data analysis and programming (e.g., Matlab, Python or R). Experience of risk assessment and/or decision analysis Experience of probabilistic methods such as Monte Carlo
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aluminium through AI-driven microstructural analysis. About us The PhD candidate will work at the Division of Data Science and AI , in the neuro-symbolic research group. This group works with combinations
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 3 months ago
performance. Throughout this PhD, the successful applicant will gain expertise in cutting-edge modelling approaches and experimental techniques including: Thermogravimetric Analysis (TGA) with Mass Spectrometry
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Organisation Job description This fully funded PhD at the University of Groningen (NL) is an independent research project titled Where Rivers Speak and Landscapes Remember. The selected candidate
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subsurface leaching into groundwater within agricultural systems experience in statistical analysis of research results or willingness to acquire such as well as to complete a PhD degree self-motivated
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longitudinal methods and cross-national data analysis to investigate the economic drivers and consequences of grey divorce. The project will explore how individual- and couple-level economic factors—such as
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necessary knowledge and a broad range of skills for the successful completion of the project. Basic knowledge of data analysis or programming and good English skills are desirable. We value independent
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aluminium in high-value products produced by mega-casting. The main objective of the PhD project is to develop a finite element analysis (FEA) framework that can accurately predict the mechanical properties