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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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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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reviewed journals (assessed at: application and interview) Ability to communicate clearly and effectively both in writing and verbally along with the ability to convey complex concepts to a range of
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Application deadline: 16 June 2025 16:00 GMT Atrial fibrillation (AF) is the most common heart rhythm disorder, but understanding its causes is challenging due to its complexity. It involves
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, this work could foster breakthroughs in drug development for AQP-related diseases. The student will build on current research to purify membrane protein ribosome bound nascent chain complexes (RNCs) of AQPs
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to ensure AI models deliver reliable, transparent, and auditable decisions in complex industrial contexts. This project offers an exciting opportunity for you to shape the next generation of industrial AI
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furnace (EAF) steelmaking. The research will support the steel industry’s transition to net-zero steel manufacturing and enhance the high-value utilisation of the new EAF steelmaking slags. Transition
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of GAGs Are confident working with complex data Enjoy learning beyond your current expertise with the support of our excellent interdisciplinary team Eligibility Start date: 1 October 2025 Open to
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introduced in workshop environments that handle many different materials, or during repair and maintenance work on complex systems where dissimilar materials are present. If materials to be joined
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substrate, enabling the layer-by-layer construction of complex 3D objects. The temperature field created by the interaction between the electric arc and the material is a critical factor influencing the