219 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"BioData"-"BioData" PhD positions in Germany
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Field
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and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team
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, in Africa and Europe. Requirements include a university degree (master's or equivalent) in archaeometry, mineralogy, or materials science, as well as the motivation to develop fundamental new data
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to work on fundamental new data relevant to archaeological research and a willingness to work in a team. A further requirement is a willingness to undertake several weeks of fieldwork (collection of raw
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sorting and data analysis Generation of single cell libraries with 10X Genomics, Singleron and BD Rhapsody platforms for ATAC, transcriptomics and multiomics assays Quality control of cells and nuclei (e.g
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data analysis is desirable but not mandatory. The successful applicant is expected to work independently as well as collaboratively within an international research team while pursuing a PhD degree
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metagenomic data) in relation to health outcomes Ability to liaise between disciplines, bridging between medical infrastructure and clinical as well as basic research Experience or interest in data analysis
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information For detailed information please see the “Call for scholarship application” .
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Max Planck Institute for Terrestrial Microbiology, Marburg | Marburg, Hessen | Germany | about 1 month ago
organization & architecture, Microbial communities & host-microbe interactions, Natural products & chemical biology, Physical biology, Physiology & metabolism, Signal transduction & information processing
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for the analysis of stable carbon isotopes in methane using the Picarro system. You will collect quantitative data for MPn in water samples from the Baltic Sea and the Warnow Estuary in order to investigate its
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Doctoral Network seeks to advance personalized medicine by developing cutting-edge AI solutions that integrate genomic, clinical, and environmental data into holistic, multimodal patient representations