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Biosafety Lab Alabama Birmingham (SEBLAB) having BSL-3 laboratories, ABSL-3 animal facility, high-parameter flow cytometry and cell sorting cores, and UAB's nationally recognized spatial omics and proteomics
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will transition in a second phase to white box approaches that result in interpretable models. For ground truth data, μCT data will be used. A similar approach will be applied using surface roughness
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phenomena such as the spread of misinformation or the formation of filter bubbles. For this, we rely on rigorous probabilistic methods to model and analyse the intrinsic complexities of these systems
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measurements under cryogenic conditions with both nanoscale spatial resolution and the ability to sensitively evaluate nanoscale heat transport over an extended temperature range (from 100 K to 300 K). To
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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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This PhD project aims to develop and apply innovative photogrammetry-based analytical tools to enhance the spatial and structural characterisation of pharmaceutically relevant materials, with a
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analytical skills for model formulation and optimization Demonstrated research potential, ideally with a track record of publications in relevant venues (journals such as IEEE T-ITS, INFORMS Transportation
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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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: Approximately 2,000 EUR/month for three years Website: IMPRS-ESM Application Contact: office.imprs at mpimet.mpg.de The International Max Planck Research School on Earth System Modelling (IMPRS-ESM) invites
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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