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energy transition, and defense economics, among others. In this role, you will work closely with advanced Ph.D. students and postdoctoral scholars from the Next-Geo program to assist them with
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Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, where we are offering a fully-funded PhD position within the DFG Priority Programme SPP2363: “Molecular Machine Learning”. About the
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institutions, the Senckenberg Natural History Museum Frankfurt. Senckenberg is as much a part of the city’s identity as its skyline and its traditional apple wine. Subsociality (parental care) is considered a
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, Bioinformatics or related fields with an interest in biology or Biological sciences with a strong background in programming Expertise and experience in programming, Python or R Expertise to work in a Linux
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- Integrating exudation into the root economics space to better understand carbon and nutrient cycling in managed grasslands” is part of the DFG Priority Program 1374 “Biodiversity Exploratories”. The project
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large environmental and ecological data sets, incl. empirical, remote-sensing and simulated model data knowledge in programming languages (UNIX, C, or similar) and script-based programming (R, Python
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a related quantitative field. You have hands-on experience in crop genomics and managing genotyping data. You bring first experience with biostatistics methods, e.g. with mixed-models. You are
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and maintaining annotation workflows (e.g., with INCEpTION/WebAnno or similar): project setup, schema management, guideline versioning, quality assurance, export/import, consistency checks. Development
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semiconductors. You should have experience working in a laboratory environment, along with basic programming and data analysis skills (Python, MATLAB, LabVIEW). High motivation, very good English or German skills
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programming, preferably Python and R, is required. Experience with mass spectrometry data, in particular metabolomics, and geometric machine learning is a plus. In addition to above-average interest in