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Field
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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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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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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 25 days ago
at Helmholtz Munich. The focus of the role will be the analysis of spatial transcriptomics and multi-omics data generated within SPACETIME. Responsibilities include data management, metadata collection and
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: Performing computational analyses of high-throughput sequencing datasets, including: single-cell RNA-seq and ATAC-seq spatial transcriptomics / spatial multi-omics bulk RNA-seq and ATAC-seq CUT&RUN Developing
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but not limited to the following: Develop new computational tools through the application of AI / deep learning / machine learning / statistics on spatial and single-cell omics (transcriptomics
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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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). Conduct transcriptomic profiling and manage single-cell RNA sequencing (scRNA-seq) datasets using bioinformatic computational tools. Assist in the transition of experimental workflows from metabolic
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agent-based models to understand how RNAs and ribonucleoprotein (RNP) assemblies regulate gene expression, cellular behavior, and subcellular organization. Integration of transcriptomics, ribonomics
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work both collaboratively and independently on projects within the CEPIO. The candidate will lead cutting-edge computational analyses of omics datasets including transcriptomics, proteomics, scRNA-seq
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are highly desirable. This includes familiarity with techniques such as single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, multiplex imaging, and other high-dimensional molecular profiling