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project Socio-Spatial Situatedness of Roman Professions and its Impact on Religion in the Roman Empire: A Formal Modeling Approach (SIPROME). The SIPROME project investigates how professions and the socio
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to study chromatin and gene regulation in mammalian cells and human disease systems. Current ongoing projects include: statistical modeling and advanced machine learning/AI method development for predicting
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of interactive web-based and/or immersive analytics environments that integrate temporal networks, heterogeneous spatial-temporal data, and AI-driven forecasting and simulation models. These environments will
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epilepsies. They use a range of advanced genomic techniques including single-cell and spatial multiomic evaluation of epilepsy surgical tissue as well as iPSC-derived neural cultures and mouse models
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will seek to understand the social conditions under which large-scale changes in norms and behaviours around accessing mobility on demand emerge. Our models will consider factors relating to social
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carried out include the pre-processing of spatial and temporal data and the implementation of Machine Learning models for the classification of fishing activity. The grant holder will also support the
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decision-support systems for sustainable forest-based supply chains in close collaboration with industrial partners. These projects aim to develop interactive methods, computational models, artificial
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spatial accuracy of approximately 5 nm and temporal accuracy of 2 to 5 ms in cell cultures on coverslips. The aim of this project is to achieve the same performance in depth in biological tissues
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interested in mammalian stem cell biology, reproduction, and development. They use cutting-edge single-cell, spatial, in vitro, and surgical approaches in multiple model species and in human organoids
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; support multi‑omics data integration and analysis across multiple research groups; and collaborate on the development and maintenance of computational pipelines for spatially resolved transcriptomics and