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Field
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its maintenance and safety increasingly depend on data. This PhD project will develop new methods that combine remote sensing, physics-based modelling, and Bayesian machine learning to support risk
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impossible scientific approaches and to pursue categorically new questions. The PhD students will develop and implement data analysis pipelines, databases, data management and open science in close cooperation
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At the University of Göttingen -Public Law Foundation-, Graduiertenkolleg Fourieranalysis und Spektraltheorie, there is a position as PhD candidate/Doctoral researcher (all genders welcome) Entgeltgruppe 13 TV-L/75
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set by the DKFZ PhD Program Strong background in molecular and cellular biology techniques, including high-dimensional flow cytometry, gene expression analysis, cell culture (2D and 3D), and
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experience with methods of molecular biology and/or in the field of histology Experience in animal experimentation is an advantage Knowledge of statistical methods for data analysis Very good written and
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the livestock sectors, climate change and policy, agricultural, food and environmental policy impact analysis, and/or production efficiency and food markets. leading to an internationally competitive PhD degree
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of provenance tracking within the workflow to enable reproducible data analysis, export to mzTab-M format Integration with EMBL-EBI BioStudies and other relevant repositories, such as MetaboLights (metabolomics
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with experience in causal inference using panel data (e.g., Difference-in-differences) solid knowledge of Stata, R and/or Python for conducting econometric analysis previous knowledge of conducting
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sets allow previously impossible scientific approaches and to pursue categorically new questions. The PhD students will develop and implement data analysis pipelines, databases, data management, and open
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using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts generated in the scattering