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Field
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of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts are supported by
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for projects examining questions in cardiovascular disease using extremely large data sets comprised of routinely-collected clinical data · Developing and maintaining requirements for access to Truveta Data and
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in this kind of environment will result in models too large to be handled and too instable to be solved. Data-driven approaches need to be used in addition to enrich the physics-based models
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targets. You will take a lead on development of computational approaches to integrate multi-omics data from patient samples, including DNA methylation, histone modifications, single-cell transcriptomics and
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RNA-seq data for testing and validation. Perform data analysis on large-scale RNA-seq data in pediatric cancer. This may involve the analysis of both scRNA-seq, bulk RNA-seq as well as new single-cell
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monitoring data and new data collected within the project. Areas and time periods with different abundances of herring will be used to investigate the role of herring in the coastal ecosystem, as prey
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Framework (RDF). enables advanced data mining queries using the SPARQL query language. provides a natural language-based interface to perform these queries on the knowledge graph using a large language model
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of mouse behavioral paradigms is required. Extensive computer programming experience in python or Matlab and the ability to deal with large, complex datasets are required. Experience with preparation and
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Continuum mechanics Large deformation elasticity Design of mechanical devices Programming skills As a formal qualification, you must hold a PhD degree (or equivalent). We offer DTU is a leading technical
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and reduction of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts