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encourage all qualified candidates, regardless of background, to apply! Job description The candidate will work on large-scale data analysis of cancer transcriptomics data (bulk, single cell and spatial), and
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and the analysis of large-scale assessment data: Methods and approaches to synthesize large data sets via meta-analyses (e.g., meta-analyses of large-scale assessment data, meta-analyses of meta
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candidate will combine methodological and substantive research. Potential methodological topics focus on meta-analyses and the analysis of large-scale assessment data: Methods and approaches to synthesize
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knowledge for precision medicine in psychiatry, building on advanced statistical methods for analysis of large-scale human genetic and neuroimaging data, to better understand how biological, psychological
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decades, as well as registry data linked to multiple large surveys with longitudinal individual-level data, school-level aggregated data, and genetic data. The successful candidate is expected to use state
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of large and complex data sets, spanning brain imaging, genetics and clinical data. The goal is to reveal more of the genetic architecture underlying brain structure and function and to improve our
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existing data linkages available in CREATE. These include linkages of registry data across several decades, as well as registry data linked to multiple large surveys with longitudinal individual-level data
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Northern Norway, Orkney and Shetland Isles, UK and undertake metabarcoding and lithological analyses of lake-sediment cores to obtain information on past vascular plant species including crops, and
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large amounts of raw data. Then the raw data must be processed in the sensor in order to be able to transmit compressed data or a condition description based on analysis of the raw data. Onboard
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especially relevant for sensor types that generate relatively large amounts of raw data. Then the raw data must be processed in the sensor in order to be able to transmit compressed data or a condition