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collaboration with the division of Geoscience and Remote Sensing at Chalmers. The project is funded by the European Research Council (ERC) under the MIXCLOUDS project, with the following objectives: -Advance our
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molecular structures capable of transferring electrons and interacting with light. Such assemblies also have applications in biomedicine. The primary objective is to develop computational methods, using deep
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risk factors. The main objective is to design and apply machine learning and deep learning methods to understand and investigate the functional behavior of gender-specific cancers. The work will include
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spatial point process models for the emergence and arrangement of objects (including birth-death dynamics, merging, and non-overlap constraints) with methods from shape analysis, in particular stochastic
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batteries. The main objective is to develop a molecular-level understanding of electrolyte degradation and to predict chemical stability by constructing reaction networks based on density functional theory
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goal is to enhance grid reliability, stability, and resilience under evolving energy system conditions. Key objectives include: Identifying and quantifying the essential grid services required