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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 hours ago
lifecycle (version control, documentation, and testing) Research experience with astronomical data analysis and large-scale astronomical survey datasets Special Physical/Mental Requirements Ability to sustain
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other projects depending on the interest of the successful candidate. Large data sets are already available for genome wide association analyses, gene set enrichment analyses, and analyses of long read
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Wide Data-Driven Circular Economy of Industrial Robots”. The candidates are expected to have experience with robotics, artificial intelligence, and digital twins. We are looking for candidates who can
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University as well as with key stakeholders from the National Forest System and state level entities. The postdoc will generate large genome-scale datasets with a variety of techniques such as Genotyping by
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, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles of climate/weather model output are advantages
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of substitution models using large dataset, successful applicants must then have a PhD and demonstrated experience in discrete choice models, machine learning techniques, big data, and optimization
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will work with existing FH patient cohort data sets from France, Portugal, Czech Republic, and Turkey, which will be expanded with multi-level multi-omics data, including genetic, transcriptomic
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climate change are far-reaching, particularly when it comes to identifying and interpreting trends in regional-to-local scale signals and extreme events. Large ensembles of climate simulations are a key
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methods. Bioinformatic Analysis (Advanced): Proficiency in large-scale omics data analysis and relevant bioinformatics tools alongside integrative multi-omics pipelines. Programming (Expert): Extensive R
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. Experience with large-scale omics data analysis and programming (R or Python). Proven track record of high-quality publications. Experience with molecular biology techniques (e.g., cell culture, CRISPR, NGS