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, metabolomics and bioinformatics secure funding through grant applications and collaborative partnerships publication of research output in international peer-reviewed Q1 journals and presentation at conferences
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software engineers passionate about developing bioinformatics tools to identify biomarkers and therapeutic targets for personalized immunotherapies against cancer. In close collaboration with other teams
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bioinformatics secure funding through grant applications and collaborative partnerships publication of research output in international peer-reviewed Q1 journals and presentation at conferences collaborate with
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omics workflows is a strong asset Previous experience working with plant systems is essential Practical understanding of bioinformatics pipelines for omics data analysis (e.g., Seurat, Scanpy, Galaxy
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of computer science, e. g. computer science, data science, bioinformatics or a related field or in the natural sciences At least 3 years of professional experience in the planning, implementation and optimization
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. Requirements: university degree (M.Sc. or equivalent) in (molecular) biology, bioinformatics, or a related field with comparable expertise by the time employment starts. We are looking for a person with
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phenotypic and genotypic analysis of newly generated overexpression and CRISPR-Cas9 knockout lines with infection assays, microscopy, proteomics, and bioinformatics, aiming to further elucidate the molecular
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | about 2 months ago
statistics Bioinformatics skills and coding (e.g. R and Python) Experience in working in a mass spectrometry facility Knowledge of liquid handling automation Experience in Lipidomics and Crosslinking-MS We
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or PhD in data science or bioinformatics with strong experience in software development for front-end and back-end solutions and research data management Knowledge in programming languages (Python, HTML
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sequencing, genetic modification, or protein biochemistry. You will work with bioinformatic tools and workflows to analyze sequencing results. Data analysis will include the use of statistical methods