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. This research project has a dual focus. On the one hand, you will be involved in analysis of spatial, single-cell and multi-omics data to efficiently characterize the different molecular layers. This will be done
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participate in internal initiatives and committees that support strategic priorities and academic excellence. Model inclusive, ethical, and professional conduct – promote a positive, culturally capable, and
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. Consequences for ecosystem services will be identified using context-sensitive spatial models developed by UKCEH for air pollution removal, urban carbon stocks, cooling etc. and for biodiversity. ii) Drivers
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Statistics or Mette Olufsen or Kevin Flores from Mathematics. Applicants with experience in Bayesian modeling, spatial statistics, mathematical modeling, data integration, uncertainty quantification and/or
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(spatial data science) and remote sensing. We have a strong track record of securing competitive funding from the Research Council of Finland, the European Research Council and private foundations, and we
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Pytorch and/or JAX deep learning models. Experience in single-cell or spatial omics data analysis. What we offerEmbedding within a computational team, with extensive experience in computational biology and
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for R and Echoview, and statistical modeling. Interest in fisheries, fisheries acoustics, aquatic ecology, and spatial ecology. Evidence of ability to work collaboratively as well as independently
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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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changes to hydrometeorological forcing. Geomorphology, 414, 108383, https://doi.org/10.1016/j.geomorph.2022.108383 Eelsalu, M., Viigand, K., Soomere, T., Parnell, K., 2024a. Systematic analysis
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work-life balance. At the division of Applied Mathematics and Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential