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Field
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(e.g., proteomics, transcriptomics, genomics, metabolomics, or related high-dimensional biological data) are desirable. Application Process You will be required to upload a covering letter/supporting
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working with human date and experience analysing large-scale omics datasets (e.g., proteomics, transcriptomics, genomics, metabolomics, or related high-dimensional biological data) are desirable
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. Current research areas include environmental and lifestyle exposures, metabolic dysfunction, obesity, inflammation, proteomics, metabolomics, and other multi-omics approaches in relation to cancer and
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spectrometry-based metabolomics datasets, with discovery of unknown metabolites being a major focus. The laboratory is engaged in several metabolite discovery campaigns involving mining of large-scale
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modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics, and metabolomics. Working closely with senior
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compliance (5%). •Conduct research on artificial intelligence (AI) and machine learning (ML) to analyze large-scale biological, genomic, metabolomic, and phenotypic dataset (25%). •Investigate the genetic
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-Sequencing, single cell ATAC-Seq, CITE-Seq, as well as bulk RNA-Seq, Proteomics, Metabolomics, and other datasets, generated from tuberculosis patient cohorts with rich clinical data. Performs advanced
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techniques such as zebrafish microbiota manipulation, molecular biology including (meta)genomics and metabolomics, bioinformatic analysis, behaviour, immunofluorescence, optogenetics and microscopy. Experience
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Sequencing data analysis will be desirable but not required. Individuals will benefit from trainings in orthotopic lung cancer and/or pancreatic cancer metastasis models, metabolomics/lipidomics, metabolic
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, pneumonia, or Tuberculosis. Implements and analyzes single cell RNA-Sequencing, single cell ATAC-Seq, CITE-Seq, Cut and Run, as well as bulk RNA-Seq, Proteomics, and Metabolomics datasets, generated from