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Previous research has examined the phenomenon of residential segregation in Berlin at a high spatial and temporal aggregation and statically, i.e. not over time. We propose a methodology to investigate the existence of clusters of residential areas according to migration background, age group, gender, and socio-economic dimension over time. To this end, we have developed a sequential mixed methods approach that includes a multivariate kernel density estimation technique to estimate the density of subpopulations and a dynamic cluster analysis to discover spatial patterns of residential segregation over time (2009-2020). The dynamic analysis shows the emergence of clusters on the dimensions of migration background, age group, gender and socio-economic variables. We also identified a structural change in 2015, resulting in a new cluster in Berlin that reflects the changing distribution of subpopulations with a particular migratory background. 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