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their CV including bachelor and master degrees, and a motivation letter detailing their interest and suitability for the position. Mission: We synthesize and test novel catalysts for sustainable energy
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within this project include: Extending DeepRVAT towards non-coding genetic variation Applying DeepRVAT to population-scale single-cell readouts Integrating population data with experimental perturbation
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phenotyping, including image analysis evaluations, for trait quantification Handle NGS datasets for RNAseq or SNP detection and linkage analysis using R Your qualifications and skills: You have a PhD or
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following position Postdoctoral researcher (m/f/d) in Environmental Data Science and Machine Learning for the project BoTiKI Location: Görlitz Employment scope: full-time (40 weekly working hours) / part
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | about 2 months ago
experimental efforts, the project will uncover new physical mechanisms and lay the foundational principles—both qualitative and quantitative—for the rational design of strongly coupled molecular systems
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available in the further tabs (e.g. “Application requirements”). Programme Description The Pre-Doc Award offers postdocs and those interested in a doctorate with a very good degree the opportunity to jointly
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atmosphere and possibilities to further extend your qualifications through educational programs within the DFG-funded collaborative research center SFB-TRR 179. The position is available from the December 1st
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this research project, state-of-the-art techniques will be employed including multi-spectral imaging, methylome analyses, RNA-Seq at single-cell and bulk levels, cell culture as well as bioinformatics analyses
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, this position can be filled part- or full-time. In the case of equal qualification, applicants with severe disabilities will be treated preferentially. Please send your application documents (cover letter
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. Prerequisites Doctoral degree with quantitative training or research experience Training and experience in quasi-experimental methods is a plus Strong coding skills in R, Stata, or other statistical software