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deployments Design a survey strategy and data analysis for the KTFZ field deployment and future missions Lead the bathymetric survey effort in the field Analyse collected dataset to inform active tectonic
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
are critical to solving key issues A good social environment with activities and routines that make it possible to talk across and enhance the collegial relationship, and where mutual trust, respect, kindness
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learning, deep learning, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific
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experience in data acquisition and analysis of advance microscopy imaging techniques (e.g. confocal microscopy, TIRF, FRET, STORM, DNA-PAINT) is desired. WE OFFER: Career development in a multidisciplinary and
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techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get unprecedented medical
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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) to advanced computational analysis. A general strong interest in quantitative approaches towards biomaterials problems is essential. Since JGU Mainz offers excellent training in various aspects
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and motivation. Ideal candidates will possess critical thinking abilities, excellent oral and written communication skills in English, and a collaborative mindset. Additionally, they should demonstrate
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, international and industrial collaborators a research climate encouraging lively, open and critical discussion within and across different fields of research a work environment with close working relationships
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field (or lab) experiments or collect observational data in the above mentioned disciplines. The candidate will develop and apply advanced data processing, signal analysis and numerical or conceptual