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generating, mobilising, and harvesting “big data” to create a dynamic and agnostic collection of information and deliver a new class of research that will enable a better understanding of the clinical
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
comprehensive quantitative evidence and understanding of their capacity and cost-effectiveness for carbon sequestration under varying conditions. You will be part of a large international research project focused
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research is based on large and high-dimensional datasets across multiple modalities, including molecular, clinical and histopathology imaging data. Our computational pathology research is based
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machine learning. The research at DTU Bioinformatics is focused on bioinformatics and computational analyses of large amounts of data generated within biological, biomedical and biotechnological and life
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in spoken and written English. Additional desirable qualifications Some experience with 'Big Data' or another complex data organization project will be preferred but not required if advanced coding
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processes. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex biological systems
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, behaving non-human primates to understand the neuronal mechanisms underlying visual attention. The position entails collecting and analyzing large datasets, writing manuscripts, and applying for grants both
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member of the larger team and for independent funding. Thus, we welcome applicants with experience in large volume serial electron microscopy (connectomics), synchrotron source X-ray imaging of brains in
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computational approaches, including artificial intelligence (AI), to unravel the mechanisms driving neuroimmunologic diseases. Your responsibilities: Plan and perform innovative large-scale experiments bridging
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systems, or network analysis. Experience with methods for causal inference, or modelling of biological systems is also considered a merit, along with prior work involving large-scale sequencing data such as