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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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cytometry, FACS, and qPCR for quantifying infection; as well as statistical analysis. You are also likely to use CRISPR/Cas9 technology, CLIP assay, co-immunoprecipitation, and other biochemical methods
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cells. Reference number: 20250273 Application deadline: August 10, 2025 Project overview This 5-year PhD project aims to develop a flexible and general model that enables comparison between different
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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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methods in applied mathematics and computational modeling, this specific project aims to uncover new insights into how blood cells form in both healthy and disease states. A key objective is to model
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hampers our ability to establish causal relations between molecular alterations and disease phenotypes. In this PhD you will address this by developing a deep learning model of cancer. The PhD position
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We are looking for a PhD candidate fascinated by the response of sensitive clays, such as quick clays that can change from solid to liquid with small environmental perturbations. We want to be able
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format. This will allow combinations of neural networks with physics models. The project brings together PhD students and senior researchers from multiple disciplines to tackle challenges in sustainable
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consist of the following: Mathematical analysis of ecological and eco-evolutionary models, involving pencil-and-paper calculations; Computer simulations of more complex models which do not easily lend
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We are now looking for our new PhD who will join us in our poject in ELLIIT , Linköping University. Your work assignments The selected candidate will conduct cutting-edge research on unconventional