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expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of manufacturing research. The Through-life Engineering Services (TES) Centre
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of this project is to develop new, scientifically valid applications of skeletal data extracted from video-based skeletal tracking for use in football. Project Objectives Compare kinematic descriptors of football
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project, which aims to develop next-generation forecasting methods combining machine learning weather prediction models with renewable energy production. The project seeks to improve the reliability and
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Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains
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and their death negatively impacts processes: for example with regards to process duration or product quality. Therefore we developed an approach that integrates the disciplines of fundamental cell and
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developing the competences of the IML group within prediction of T and B cell immunogenicity and immunoinformatics in general. You will work with nearby bioinformatics, postdocs and PhD students working
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devices that can operate in confined anatomical environments and interact with biological tissue with high spatial precision. This PhD project focuses on the development of surgical micro-robotic devices
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microscopy for probing matter at the atomic scale. Our primary objective is to develop a novel electron phase reconstruction technique based on momentum-resolved scanning transmission electron microscopy
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will be centered on further developing the competences of the IML group within prediction of T and B cell immunogenicity and immunoinformatics in general. You will work with nearby bioinformatics
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commercial models that may best support this transition. In doing so, the research will assist airports in their long-term development strategies and support them in planning for the introduction of hydrogen