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Field
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execute bacterial perturbation experiments, develop scalable molecular biology workflows, and generate high-quality transcriptomic, physiological, proteomic, and metabolomic datasets. This position offers
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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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, biostatistics, computer science, biomedical informatics, genomics, systems biology, quantitative biology, or a related field. Demonstrated experience analyzing genomic, transcriptomic, or other high-dimensional
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candidates with experience in one or more of the following areas, cell line editing (CRISPR-KO and knock-in base editing), NK and cytotoxic T cell co-culture assays, single-cell transcriptomics, HLA
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. Utilize digital pathology, computational pathology, genomic, and transcriptomic approaches to analyze tissue cohorts for translational biomarker discovery projects. Contribute to tissue biobanking and
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focus on positive and proactive mentorship, teamwork, and scientific creativity. The Hallegger lab addresses the question of what proteomics and transcriptomics changes are linked to the earliest stages
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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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(plant) molecular genetics, microscopy, and cell biology are required. Previous experience with model grass species, (plant) signalling, protein biochemistry, or single-cell/spatial transcriptomics is an
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-generation sequencing and single-cell technologies (e.g., scRNA-seq, scATAC-seq, scTR-seq, and/or spatial transcriptomics). Previous experience in both Bioinformatics/Genomics and Cancer Biology is desirable
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cancer models Experience with single-cell/single-nucleus genomics and spatial transcriptomics Computational analysis skills in R and/or Python A record of first-author publication To apply: Please send a