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, pharmacology, genomics and multi-omics, as well as growing methods in advanced analytics of health data e.g. machine learning to improve human health with a focus on therapeutics. These posts will work alongside
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proof-of-concept study using protein A resin (as a model resin), 2 IgG product streams produced by a platform CHO cell lines and advanced analytical methodology (including LC-MS, ELISA and CE-SDS
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Generation Sequencing pipelines (single-cell RNA-Seq, single-cell ATAC-Seq, spatial transcriptomics analyses etc...). Excellent critical thinking, research, and analytical skills. Excellent communication and
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fragmentation approaches utilised in the field of proteomics; the ability to carry out analytical procedures that are applied for proteome characterisation to a high degree of precision; able to analyse
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methods. The ability to carry out analytical procedures that are applied for proteome characterisation to a high degree of precision including sample preparation, LCMS and data analysis is also essential
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Carrasquillo Lab, National Center for Complementary and Integrative Health, National Institutes of Health | Bethesda, Maryland | United States | about 1 month ago
with strong molecular, computational, or transcriptomic backgrounds are especially encouraged to apply. Other requirements include strong laboratory, analytical, and organizational skills; excellent
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recordings, intracranial stimulation studies, and sleep evaluations. Apply quantitative and analytical approaches to interpret multimodal research data. Utilize programming and data analysis tools such as
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, or related biodiversity forecasting approaches; advanced programming skills in R and/or Python and experience with reproducible analytical workflows; experience handling large geospatial, biodiversity
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problem-solving and analytical skills High degree of computer and internet literacy, including excellent working knowledge of MS Office Suite Superior oral and written communication skills; ability
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knowledge of data analysis and processing, programming, and development of analytical models. Experience with databases and quantitative analysis tools. Ability to work with large datasets and computational