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Postdoc in Generative Machine Learning for Biomedical Data | Human Technopole, Milan Build the science that shapes the future of human health. Application closing date: 21.02.2026 Join a place where
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advanced statistical analysis, pathway & network analysis, Integrating complex clinical, biological and molecular data. Contributing to data visualization, figure generation and interpretation
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within DanSIC and CIMP. Collaborate with internal and external researchers to design experiments and analyze complex datasets. Perform statistical analyses and data visualization to interpret and publish
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within the University of Münster developing imaging methods allowing to visualize molecular processes inside organisms, tissues and cells. With the help of imaging, we perform cutting-edge research in
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fluorescent reporters to visualize subcellular protein localization and to monitor cellular dynamics or metabolite levels in plant tissues Demonstrated experience in performing β-glucuronidase (GUS) reporter
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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to collaborate with industry (biotech/pharma) and to get involved in academic start-up/spin-off companies. Training program in project management, scientific writing, visual communication, entrepreneurship
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sequencing; Has experience with programming, data visualization and data handling in Python, R or related languages; Is proficient in Unix/Linux-based command line and cluster environments; Has
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. ⦁ Skilled in R programming for statistical analysis and data visualization is plus ⦁ Ability to work independently and collaboratively in a multidisciplinary environment. ⦁ Excellent written and verbal
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interactions:(1) We propose to study the realization of more complex tasks than textual answers generation to include the generation of graphical widgets and data visualization means when appropriate