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Field
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to model and analyse the intrinsic complexities of these systems. This research direction requires advancements in modern probabilistic tools, including spatial random graphs, random walks, and Markov chains
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and accepted to the PhD program at Stockholm University. Project description Project title: “Deep learning modeling of spatial biology data for expression profile-based drug repurposing”. A new exciting
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. Spatial Transcriptomics: Application of Spatial Transcriptomics to new patient samples with the aim of validating the molecular signature of the cell populations identified by the AI using Giemsa morphology
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models considering networks of patches and their species and interactions composition to predict spatial and temporal community structure across restoration gradients, aimed at developing a predictive
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temperature stability and spatial resolution, to make a leap in this field. The PhD research programme will squarely address these challenges. The PhD candidate should have completed (or about to complete
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spatial and temporal patterns) to understand the effects of varying climatic conditions on post-fire recovery, and evaluating spatial recovery patterns across different elevations, slopes, and forest types.
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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changing spatial regulations. You will also help design economic decision-support tools to inform more inclusive and evidence-based marine policy. Your duties and responsibilities include: analyzing
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of the Earth system at different temporal and spatial scales to improve predictive capability. Comprehensive education: Enjoy numerous opportunities for scientific training, skills development and problem
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on the subcellular spatial and temporal dynamics of these interactions, with an effort to resolve how different pharmacological approaches may strategically and uniquely alter them. The position is limited to a period