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-scale Microflora Danica dataset combined with samples taken from sites. You will conduct sampling, and apply experimental methods such as metagenomics and metatranscriptomics, linked to soil process data
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metatranscriptomics, and the development of predictive models of the soil microbiome. The role: The principal role of the position will be to develop these computational methods. These will include bioinformatics
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biodiversity, structure, and functions of communities associated with biocrusts. Field surveys, physicochemical soil analyses, controlled experiments, DNA metabarcoding, metatranscriptomics, and bioinformatic
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these communities influence pathogen persistence, sanitizer tolerance, and antimicrobial resistance. The work integrates shotgun metagenomics, metatranscriptomics, genome-scale metabolic modeling, and culture-based
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-throughput multi-omics data (16S rRNA, metagenomics, or metatranscriptomics) in environmental or biological systems. Computational Modelling: Proven experience in computational modelling, algorithm development
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. The position will conduct metabarcoding, metagenomic, and metatranscriptomic analyses of samples collected from sites, and lead research expeditions to collect new samples across the growing season (March-May
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with the following project: EARLYPTB “DIGITAL PCR AND GENETIC, TRANSCRIPTOMIC, METATRANSCRIPTOMIC AND EPIGENETIC CHARACTERISATION TO IMPROVE EARLY DETECTION AND GENETIC RESISTANCE TO PARATUBERCULOSIS
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analysis Microbiology knowledge and technical skills in microbiome analysis, including metagenomics and metatranscriptomics Proven commitment to proactively keeping up to date with discipline knowledge and
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sequencing, metagenomics, metatranscriptomics, proteomics, 16S sequencing, transcriptomics and epigenetics. Experience in integrated multi-omic analysis and patient-based data, including dealing with missing
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 3 months ago
, metatranscriptomics); Good knowledge of statistics; Basic knowledge in applying AI-based models (e.g., machine learning, predictive modeling) for the analysis of biological data; Very good command of English (spoken