MSc Research Internship

2 weken geleden


Nijmegen, Gelderland, Nederland Max Planck Institute for Psycholinguistics Voltijd

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 ). 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 ). 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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