Build and manage omics datasets (particularly bulk and single-cell RNA sequencing data) to support hypothesis generation and mechanistic insights • Perform target discovery and biomarker identification analyses using computational and statistical approaches
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Laufendes Masterstudium Bioengineering/Bioprozesstechnik oder Verfahrenstechnik / Chemieingenieurwesen, Bioinformatik, Biotechnologie, Molekularbiologie (oder vergleichbar) … Erste Erfahrung mit Simulation/CFD (keine Voraussetzung; kann im Projekt erlernt werden)
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Build and manage OMICs datasets (in specific bulk and sc-RNAseq) to support hypothesis generation and mechanistic understanding - Perform target discovery and biomarker identification analyses using computational and statistical approaches
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lllumina short-read mapping, variant calling, joint genotyping - Population structure analyses - Genome-wide association analysis for target traits, machine learning methods for classification and prediction of phenotypes - ldentification of candidate genes/regions and variants as markers for breeding and validation
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lllumina short-read mapping, variant calling, joint genotyping o Population structure analyses o Genome-wide association analysis for target traits, machine learning methods for classification and prediction of phenotypes o ldentification of candidate genes …
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In this position, you will play a key role in data management and science communication within the MYCOS PhD program. Your tasks will include: - Data curation and management: Maintaining, structuring, and standardizing datasets for the MYCOS consortium
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Applicants should be highly motivated and have an outstanding interest in brain development and neuroscience. Experience in molecular biology and cell culture is essential. Bioinformatics experience (or general programming skills in Python and R) is an advantage
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52 Faculty of Chemistry - Job vacancy starting: 05/01/2026 | Working hours: 30,00 | Classification CBA: §48 VwGr. B1 Grundstufe (praedoc) … The project combines state-of-the-art molecular biology, analytical chemistry, and bioinformatics approaches
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Detection and analysis of large structural variation via pairwise whole-genome comparisons and based on short-read and long-read sequencing data; benchmarking of existing methods and implementation of improved workflows - Application of machine learning methods to identify taxon- and cultitype-specific structural …
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lllumina short-read mapping, variant calling, joint genotyping - Population structure analyses - Genome-wide association analysis for target traits, machine learning methods for classification and prediction of phenotypes - ldentification of candidate genes/regions and variants as markers for breeding and validation
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