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vivo models, immune–metabolic signaling, flow cytometry, and cell death or redox biology. Experience with single-cell or spatial transcriptomics is highly desirable. Independent yet collaborative
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developing approaches to leverage spatial data to better understand evolutionary histories. More information about the lab and their work can be found by visiting https://federlab.github.io/ About the
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high content imaging, multimodality in vivo imaging, proteomics, spatial and single-cell transcriptomics. As part of King’s Health Partners, we have an excellent environment for basic-clinical
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the services nature provides to people. The position will combine ecological data analysis with statistical and spatial modeling to quantify chemical impacts across multiple levels of biological
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the social and environmental implications of proximity models, combining spatial, mobility and socioeconomic data to develop indicators and tools for the toolkit. The candidate will also assume coordination
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transplant rejection through cutting-edge spatial multi-omics and computational metabolic modeling. The role involves developing and implementing computational methods to integrate single-cell and spatial
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PhD in a relevant field (e.g. political science, statistics, computer science, informatics, economics, or related discipline) with a demonstrated focus on forecasting, statistical modelling, and/or
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the spatial and temporal transferability of the models. • Projection of the relationships obtained in future climate scenarios using ADAMONT projections to assess how gravitational crisis episodes will evolve
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Position as Computational Analyst / Bioinformatician in RNA Therapeutics and Cardiometabolic Disease
of (micro)RNA biology, 3D human model systems, nanomedicine, and computational (ML) disease modelling. You will be able to contribute to our vision to translate basic findings into medicinal RNA approaches
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the intersection of mucosal immunology, cancer, and spatial transcriptomics, with the ultimate goal to understand and harness immune responses in human diseases. The Engblom and Villablanca labs form a tight-knit