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the properties of post-consumer recyclates. The project will apply cutting-edge data science techniques, including principal component analysis and machine learning, to handle multivariate datasets and enhance
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Steel and other metal alloys. Other raw materials (i.g. Construction materials) Electronic and photovoltaic materials Research study area 1: The first research focus will be the application of advanced
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research will focus on the design of this network as it evolves, and verification of its performance, or specific aspects of it. It will involve, as one component of the research, developing the Claims
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donated to research. Our recent data demonstrated successful delivery of homodimeric minimal Factor H during the cold flush period of the organ transplant pathway, which protected human organs for damage
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critical component analysis, and (iii) development of Automation of ML model and data selection. The applicants should have knowledge of machine learning and optical networks and willing to engage in testbed
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produced contain the therapeutic element; iv) Challenging downstream purification with low yields due to the similarity between the desired product and the product-related impurities .The proposed project
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, complexity, and verification needs. By mapping each component to the most appropriate FM tool based on cost-efficiency and expected reliability gains, we aim to construct validation portfolios: automated
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collection design and method. Remote Working: Is this project suitable for remote working? Yes Remote working details: This project could be done remotely but the fieldwork component would need to be
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thermal-catalytic system and nonthermal plasma system will also be investigated. The project will involve the preparation and modification of porous materials (e.g., zeolite, MOFs, metal oxide) and
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. Generating gastruloids from induced pluripotent stem cells (iPSCs) to create in vitro models for studying critical steps of gastrulation and early development. Creating iPSC lines with mutations in elements