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subsequent precipitation hardening process. In addition, promoting a circular economy in the aluminium industry by increasing recyclability and using more recycled aluminium is essential for saving resources
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine
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engagement skills, your interest in the research topic, and future career plans. Full guidance on the application process is available here. Early applications are encouraged. The post is preferred
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an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine learning techniques and experience with coding in Python is beneficial (but not a strong requirement
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protocols for electrical biasing of samples in the microscope. A key task is to process and analyse large 4D-STEM data sets and extract information about domain wall structure and dynamics. The role involves
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: Equality, Diversity and Inclusion (EDI) – We encourage applications promoting and embedding EDI values throughout the whole research process. We also encourage original research addressing key EDI-related
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Dr. Lucy Vanes (lucy.vanes@kcl.ac.uk ) for more information regarding the project and studentship. If you have any queries regarding the application process, please contact the Education support team
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process, please contact the Education support team at ioppn.pgr@kcl.ac.uk . References must be received by the deadline for the applicant to be eligible. Only shortlisted applicants will be contacted.
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throughout the water/wastewater value chain, allowing for more informed and robust strategies toward sustainability and circularity. Skills/Experience Required: Process systems engineering, wastewater
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inequalities shape carers’ lives using qualitative and creative methods (e.g. Theatre of the Oppressed, or others). 2) To support the co-production process across our team and partner organisations (e.g. Black