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individually, make a real difference. The role A research fellow position is available to work on the project “Dynamic and Adaptable Monitoring of Greenhouse Gas Emissions with Robots” funded by the UKRI Natural
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of hydrological data and modelling Ability and enthusiasm to engage with stakeholders and partners across the water sector Strong analytical and coding skills within a package such as MATLAB, R or Python. Ability
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completion to deadlines. Develop scripts and data processing pipelines using R or Python, leveraging advanced expertise for data processing, model development, and data visualization. Work with senior staff
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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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mimicked with in vivo models of metastasis, which provides unique opportunities to mechanistically dissect what drives the different cell states. You will link clinically relevant phenotypes to putative
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, with a focus on biodiversity conservation. You’ll contribute to high-impact publications and collaborate across disciplines to deliver research that makes a real-world difference. In addition a
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to validate the effects of candidate variants, such as CRISPR-based gene editing or RNA-seq to assess gene expression changes, and linking these findings to clinical phenotypes. • Examining Differences in
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Vibrant campus life with a strong sense of community & inclusion Enjoy a career that makes a difference by collaborating & learning from the best At UNSW, we pride ourselves on being a workplace where the
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. The postdoc (M/F) will contribute to different research aspects on the project: • Develop, implement and apply ecological modelling tools (bioenergetics, thermodynamics, ecological modelling, individual-based
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. The postdoc (M/W) will contribute to different research aspects on the project: • Study/analysis of cryosphere (cryoconite, ice, sediment, soil) environments and microbiomes (experimental and observational