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Job related to staff position within a Research Infrastructure? No Offer Description Challenge: Unravel storm–lake coupling at fine scales. Change: Combine unique observations and cutting edge models
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differential equations (PDEs) and modelling with PDEs. More information on ongoing research at the department can be found here. Each year, LTH admits more than 1000 new students to its engineering programmes
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. Ali Bashashati). Responsibilities Designs and implements machine learning models for bulk and single-cell genomics and transcriptomics. Analyzes spatial transcriptomic datasets to uncover tissue
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, and spatial organization, crucial especially in early developmental stages but relevant throughout life. Drawing from cellular and molecular biology, it delves into embryology, morphology, genetics
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analysis pipelines and to integrate imaging data into computational models. It is an opportunity to work with research groups across the Cell-Matrix Centre and the Bioimaging Facility. The appointee will be
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well as in liver regeneration and cancer. Leveraging publicly available spatial datasets, this project aims to develop data-informed computational modelling and systems biology framework to dissect molecular
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exhibit hallmarks of active matter. This PhD project aims to develop theoretical and computational active-matter models of early mouse embryogenesis that couple collective cell mechanics with gene
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such as R, SAS, ArcGIS, SQL, Python and AI tools. Conducts geospatial and epidemiologic analyses relevant to the catchment area to assess cancer outcomes, spatial patterns, temporal trends, and disparities
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starts. Preferably, you will also have: Interest in global water issues and earth system modelling; Strong quantitative methodological skills, for instance knowledge of (spatial) data analysis
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-cell sequencing and spatial transcriptomics is preferred. This position will be an excellent opportunity to gain experience performing basic and translational research using patient-derived specimens and