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Field
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project was selected for funding by the European Research Council (ERC) and is led by Prof. Anna Korhonen. The goal of the project is to investigate the challenges in the development of globally inclusive
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for analysing complex materials, structures and model validation. The DIC community has developed guidelines to ensure robust measurements, continually advancing standards through ongoing challenges. In
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, engaging with key stakeholders (e.g., technologists, citizens and governments) to build an understanding of their needs. Based on these findings, you will design and develop e-governance systems
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: Framework Development: Design and implement a generative deep learning framework for cross-modal integration and analysis, resilient to distribution shifts. Correlation Discovery: Identify interpretable
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microstructure exhibiting improved physical and mechanical properties. The main objective of this project will be to develop a mechanistic understating of the microstructural evolution of the Additive
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. This project seeks to advance energy autonomy by optimising power conversion, storage, and distribution in such systems, enabling broader adoption in real-world applications. The project aims to develop a PMC
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 3 months ago
. Unlike natural gas, which has a constant composition, CO2 streams are project specific and contain over 20 impurities across gas, liquid, and supercritical phases, complicating the development
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bottlenecks facing flexible and large-area metal oxide electronics: the scarcity of hole-transporting (p-type) oxide semiconductors. Developing p-type materials with performance on par with their commercialized
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performance. However, calculating defect formation energies and migration barriers using first-principles methods remains a major bottleneck in the materials discovery process. To address this, we will develop
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are not limited to): The development of AI-related skills and competencies for project practitioners The factors influencing project managers’ and organizations’ willingness to adopt AI applications