Emerging models in biology show the major role of molecular dynamics in cell regulation mechanisms. Measurements in living cells are hampered by the complexity of the biological system: heterogeneity, large number of molecules, different spatiotemporal scales; and there is currently no microscopy device capable of addressing this wide range of dynamics. We have previously shown that fluorescence fluctuation (FCS) and single molecule tracking (SPT) measurements carried out separately demonstrate the existence of populations diffusing with different spatio-temporal scales (0.1 to 10 um2/s) but do not allow not to understand the underlying mechanisms. For this, it is necessary to develop a device coupling simultaneously these SPT and FCS measurements (2 possible options: single channel or multi-points), with analysis tools integrated into the acquisition process allowing a better exploitation of the multimodal measurements and to perform cross-analyses of these data with weak a priori. In this project, we propose to design an original approach coupling multimodal SPT/FCS instrumentation and dedicated image analysis relying on deep learning. We will develop an acquisition and quantification workflow based on multi-dimensional measurements (us to ms and 0.2 um to 10 nm). Our objective will be to apply this measurement chain to study the spatio-temporal dynamics of RNA polymerase II. This project will constitute a real breakthrough in the measurement and interpretation of molecular dynamics in cells. It is innovative for: 1) instrumentation: simultaneous FCS/SPT acquisition; 2) analysis: development of data processing and analysis methods allowing the extraction of correlated results between different spatiotemporal scales; 3) methodology: collaboration between instrumentalist, modeler and image analyzer in an organization based on the multidisciplinarity of the consortium.