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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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phosphonate linkers preparation and crystallization of new MOF structures advanced synthetic methods, including work with air-sensitive compounds (Schlenk techniques) comprehensive characterization of materials
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have partnered with AWE to fund a 4-year Computational Project to use state-of-the-art Computational Chemistry techniques to understand structure-property relationships in oxide scintillators. We will
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counterintuitive situations, facilitated the construction of acceptable masculinities and fantasies of post-war British identity. Contact Informal enquiries regarding this scholarship may be addressed to Professor
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computational work involves protein structure prediction Publications in high impact factor journals Knowledge and experience in AMR, Artificial Intelligence in health and food systems Good laboratory skills
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with the industry partner A structured professional development and training program to develop your applied research skills The project is entitled “Project 2: Techniques and Frameworks for Enabling
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explore how salt distribution, structure formation, water management, and flavour release interact during processing, cooking, and consumption. Using advanced characterisation tools alongside sensory and
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. Are you ready to take your next step? We welcome curious minds from all backgrounds. Course organisation At DIGS-ILS, PhD training is structured but flexible — designed to support independent
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, material properties and formulation behaviour, the project will explore how implant structure can be designed to regulate drug transport and provide sustained therapeutic release. The overall aim is to
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the most comprehensive overview of SMARTs to date and highlights several important common problems. First, sample size calculations rarely reflect the multistage structure and the intended treatment‑sequence