This outstanding opportunity to receive training in the newly emerging field of Sociogenomics is part of the Marie-Sklodowska-Curie-Actions (MSCA) by the European Union for doctoral education. Under HORIZON EUROPE, a network of 8 Universities is emerging, offering 13 PhD positions to include genetic data in the study of the social sciences. In this network, this project falls under the Research Objective focussing on the questions: How important is the nature-nurture interplay in causally shaping life chances? The project will rely on whole-genome, molecular genetic data and, theoretically driven, will apply data reduction techniques to integrate genetic information into social statistical models. It will furthermore apply big data econometric models.

Objectives: How much of the individual differences in educational attainment in our societies can we explain with our ever-growing data sources – and how? We don’t yet have the answer. Is this a problem you can solve? Recent methodological advances highlight the potential of mixed-linear models in improving explanations including very small effects and higher-order interactions. In contrast to machine learning approaches, these methods have more statistical power and are parametric. In this project, you will apply theory-driven big data econometric models as well as data reduction techniques (Polygenic Scores) to integrate genetic and social information and model their interplay to figure out how (much) educational inequality in our populations is explainable by gene-environment interaction and correlation. With the TwinLife study, we provide a unique, interdisciplinary dataset including molecular genetic and epigenetic data based on a series of saliva samples in a family study – next to details and longitudinal social survey data. You’ll be part of a training network across Europe and be ttraveling for conferences and classes to meet your fellow PhDs and exchange ideas.

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