Postdoctoral Researcher Department of Child and Adolescent Psychiatry Psychology

The project is part of a large European-funded consortium, called FAMILY, involving multiple national and international institutions and the analysis of data from a range of human cohorts (both from the general population and high-risk studies of offspring with a parent suffering from mental illness). As part of the FAMILY consortium, the postdoctoral researcher will have the unique opportunity to access data from the largest neonatal epigenetic cohorts in the world, including Generation R (GenR), Avon Longitudinal Study of Parents and Children (ALSPAC) and The Norwegian Mother, Father and Child Cohort Study (MOBA), encompassing ca. 10,000 participants with epigenetic profiles. All cohorts include a wide range of data on parental mental health, genetic and environmental factors as well as child neurodevelopmental, cognitive and mental health outcomes into adolescence.

The pooling of individual level data from multiple studies creates an unprecedented opportunity to construct reliable and generalizable transmission load profiles. The multi-center design, large sample size and wealth of exposure and outcome data available as part of this project, will allow the postdoctoral researcher great power and flexibility to construct transmission load scores and test their predictive ability. The intention is to both employ traditional statistical methods used in epigenome-wide association studies, as well as to explore innovative machine-learning methods, such as deep neural networks and the application of genetic trio designs. The postdoctoral researcher will have freedom to determine which approaches to test under guidance of the supervisors. The postdoctoral researcher will be responsible for data cleaning/QC, data analysis, write-up and publication of results in peer-reviewed literature. The candidate is required to have experience and a good grasp of applying standard analytical methods to large, high-dimensional datasets, ideally genome-wide (epi-) genetic data. The postdoctoral researcher will also need to independently explore, learn and test modern machine-learning approaches. Proficiency in statistical programming is therefore a prerequisite, and experience with machine-learning methods desirable, but can be also acquired during the project. A budget for training and travel costs is available for these and other purposes, such as conferences. The candidate is expected to share results of their research in traditional peer-reviewed literature, but also to actively participate in open science culture, e.g., by sharing analysis scripts, summary data, or open-source R packages. The ideal candidate is passionate about increasing our understanding of psychiatric disorders and about the development of perinatal prediction systems.

While the postdoctoral researcher will be working with multiple international studies, they will primarily be embedded within the Generation R Study, a unique Rotterdam-based birth cohort that started in 2002 and has been following the lives of nearly 10,000 children across development. This will be done in close collaboration with the Departments of Epidemiology and Pediatrics, as well as with national and international research groups. The PhD student will be supervised by Dr. Alexander Neumann, senior researcher in Generation R, Dr. Charlotte Cecil, Director of the inDEPTH Lab and Team Leader of the Biological Psychopathology research line in Generation R, and Prof. dr. Neeltje van Haren, Professor of Brain Development and Psychopathology as well as Coordinator of the FAMILY consortium.