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biology techniques, cell culture, microscopy, tissue processing, immunohistochemistry, immunofluorescence, data analysis (gene expression data, flow cytometry data, etc). While our research is primarily
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, it will be important for candidates to have familiarity with basic coding practices to coordinate data collection across multiple platforms (e.g, coordinating calcium imaging or optogenetic delivery
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), deep learning, and multimodal data integration. The ideal candidate will be able to design and apply AI/ML approaches to high-dimensional datasets, including single-cell omics, chromatin profiling, and
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well as to allow video information to be shared for both marketing, analytics and editorial purposes. By accepting optional cookies, you consent to the processing of your personal data - including transfers to third
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The Centre for Machine Learning within the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark invites
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measurements A good understanding of advanced physiological techniques Experience with enzymatic in vitro assays and plant x climate interactions Experience in complex data handling and statistical analysis
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Research Associate (f_m_x) - Political and Social Sciences, Spatial and Planning Sciences - LINK ...
Zwillingen, UDZ) The project develops and tests Urban Digital Twins as tools for climate adaptation and sustainable urban development, with a particular focus on digital sovereignty, interoperable data
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of this position is to bring together microbiology and biogeochemistry to effectively integrate biological and biogeochemical data that stem from laboratory incubation experiments to large scale environmental
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increasing independence over time. Collaborate on project and analysis design guided by their PI. Develop new computational methods. Adhere to field and lab standards for data analysis. Identify, process
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that are calibrated to measurement data. We are motivated by applications in engineering in which the system models are partial differential equations (PDEs) with potentially infinite-dimensional (e.g., space-dependent