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Field
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requirements: First-class or upper second-class degree (or equivalent) in Chemical/Process/Electrochemical/Mechanical/Electrical Engineering, Chemistry, or Physics, or relevant industrial experience
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Funding providers: The FSE Doctoral Focal Award, Swansea University and Leaf Tech Ltd The subject areas: Materials Science, Chemistry, Chemical Engineering, Electronics, Mechanics, Polymers, other
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engineering with an emphasis on developing and refining processes which must be compatible with large scale manufacturing. The successful applicants will expect to split their time between the Swansea Bay
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based on combustion engines, which plays a crucial role for sustainable development and Net Zero. Power electronics converters is a key enabler for vehicle on-board electrical power conversion. Therefore
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an industry partner you will conduct a series of investigative processes (e.g. systematic reviews, meta-analyses, observational and intervention studies), to evaluate the efficacy and current usage of different
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crosslinking agents. This initiative combines the expertise of a leading global battery R&D organisation and a specialist in polymer chemistry to develop GPEs with superior ionic conductivity and interfacial
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of IR efficiencies like heat pumps. Currently the Standard Assessment Procedure (SAP) attributes infrared heating the same CO2 equivalent as direct electrical heating. However, it is currently unclear
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been previously unavailable and could benefit the broader biomedical community, including the pharmaceutical industry. Qualifications Master-level degree in electrical engineering, physics, mechanical
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 3 months ago
technologies tailored to CCUS needs. Accurate knowledge of CO2 streams density is vital across the CCUS chain, impacting engineering design, pipeline safety, reservoir management, and financial settlements
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engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early