MSc Research Internship (5 months) – Max Planck Institute for Psycholinguistics – Nijmegen

Max Planck Institute for Psycholinguistics

The Max Planck Institute (MPI) for Psycholinguistics, Nijmegen, the Netherlands, is offering a 5-month MSc internship position in the population genetics of human communication group (https://www.mpi.nl/department/population-genetics-human-communication/11). The host research group, led by Dr Beate St Pourcain, is embedded within the Language & Genetics Department at the MPI. Research within the group focuses on (i) studying the genetic basis of social communication, language and interaction in population-based and clinical cohorts and (ii) developing statistical modelling approaches.

Job description

In this biostatistics research internship, students will work with the Genomic-Relationship-Matrix Structural Equation Modelling (GRM-SEM) framework1,2, an R software developed by the host research group (https://gitlab.gwdg.de/beate.stpourcain/grmsem). GRM-SEM can be used to model genomic and residual covariance structures, as captured by genome-wide data, with SEM strategies analogous to multivariate twin models. For example, our group applied GRM-SEM to study genetic relationships among language and literacy traits during different stages of development3,4 or to investigate symptom differences among autistic individuals5. However, within a study population, groups of individuals may often differ from each other and genomic structures may, thus, vary, such as, for example, between males and females. Therefore, a uniform model across all individuals may only be partially informative.

This internship aims to develop the GRM-SEM framework further, allowing (i) the joint modelling of multiple groups within a study sample (multi-group model) and (ii) optimising current genomic and residual modelling strategies using simulations and benchmark tests.

Requirements

  • MSc student enrolled on a master’s programme such as Computer Science, Biostatistics, Statistics, Genetic Epidemiology or similar
  • Solid background in undergraduate statistics
  • Good programming expertise in R and bash or another programming language (e.g. C/C++, Python)
  • Good knowledge of English
  • What we offer you

  • Experience in modelling genomic and residual structures as captured by “big data” from population-based cohorts using GRM-SEM software
  • A nice team
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