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of handling, cleaning and integrating complex genetic and molecular phenotype data into epidemiological datasets (pipelines); Working with epidemiologists and other colleagues in the Centre to help develop and
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, cleaning and integrating complex genetic and molecular phenotype data into epidemiological datasets (pipelines); Working with epidemiologists and other colleagues in the Centre to help develop and implement
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gender equality plan and the cascade model measures, which we actively implement to enable sustainable equal opportunities in academic career paths. The GFZ thus committedly strives for gender equality in
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positions. We among others do this through our gender equality plan and the cascade model measures which we actively implement to enable sustainable equal opportunities in academic career paths. The GFZ thus
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! PROJECT: The project entitled ‘Dynamic cues guiding postnatal germline development in marmoset‘ focuses on single-cell transcriptome analysis of germ cell development in a non-human primate model. In
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evolution, and further to modelling. Investigating transcriptional profile of lncRNA. It can be expression quantification, alternative splicing, start sites properties. Performing AI modeling and developing a
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neuroimaging and mc-tCS simulation approaches based on realistic head volume conductor models using modern finite element methods as well as sensitivity analysis. The new methods will be applied in close
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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of Southern Denmark, Vienna, and Gothenburg, as well as Carnegie Science, and synergistically integrates innovative oceanographic, biogeochemical, ecophysiological, and model-based investigations. The position
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 2 months ago
, mathematics, and data science. Collaborative projects merge traditional geographic research with advanced computational methods such as graph neural networks (GNNs) and large language models (LLMs) to explore