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, they are characterizing how spatial organization shapes these evolutionary outcomes and developing approaches to leverage spatial data to better understand evolutionary histories. More information about the lab and their
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Position as Computational Analyst / Bioinformatician in RNA Therapeutics and Cardiometabolic Disease
Responsibilities: Benchmarking existing and developing novel computational approaches for inference of microRNA activities from single-cell/nucleus and spatial omics (NGS, MassSpec). Interrogation of GWAS data
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expertise, including facilities for high-throughput screening and high content imaging, multimodality in vivo imaging, proteomics, spatial and single-cell transcriptomics. As part of King’s Health Partners
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editing, mouse modeling, iPSC disease modelling, cell sorting, live cell imaging, spatial and single cell omics modalities, and advanced image processing and analysis, amongst a variety of other specific
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interpersonal and communications skills. Qualifications Mandatory: PhD in related field Desirable: Experience in spatial analysis, proteomics. Please Note: Appointment to this position is subject to passing a
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-methods framework for participatory analytics that integrates climate and health data, intersectional multi-level analysis of vulnerabilities, and participatory action research. A central aim is to
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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of High-Throughput Mass Spectrometry Data, Single-Cell and Spatial Omics Data Analysis, Biomedical Data Integration and Visualization, Computational Systems Biology and Network Medicine, Computational
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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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of large spatial and temporal biodiversity datasets. Since almost 20 years the Rhine-Main-Observatory (RMO; https://www.senckenberg.de/rmo/ ) has been part of the German LTER network (https://www.ufz.de/lter