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Field
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reliability and operational efficiency. Determining the optimal size and location of PSTs within a network is inherently complex due to the nonlinear and dynamic nature of power systems, necessitating the use
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can be varied. Crucially, the models we derive will be validated by real-world measurements to ensure our simulation environments are realistic and scalable to more complex radar networks. This will
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Overview: As data becomes more accessible, new challenges arise around how best to use it—especially in complex, multi-system environments like aerospace. Ontologies offer a powerful solution by
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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-enhanced exact methods, particularly focusing on Column Generation (and Branch-and-Price), to improve scalability and convergence in solving complex optimization problems. In collaboration with your
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the genetic factors influencing changes in brain structures, using brain imaging, computational and statistical methods of network science. Project Aim: The aim of the project is to uncover the complex
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, Heidelberg and Mannheim, our researchers harness interdisciplinary collaboration to decipher the complexities of disease at the systems level – from molecules and cells to organs and the entire organism
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to avoid abrasion and agglomeration. A small-scale experiment will be devised to explore some of the complexities. There will be issues of supersonic flow and how the presence of an abrasive fluid affects
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to avoid abrasion and agglomeration. A small-scale experiment will be devised to explore some of the complexities. There will be issues of supersonic flow and how the presence of an abrasive fluid affects
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Project Description: This funded Humanities PhD project will be conducted as part of the new Centre for Net Positive Health and Climate Solutions. The project will focus on cultural histories of eco