The
PersonalRiskProfile project aims to develop advanced genetic prediction methods to improve early identification of individuals at risk for serious mental illness.
Serious mental illness has a major impact on patients, families and society. Early recognition of elevated risk creates important opportunities for prevention and timely intervention. Genetics has strong potential to improve risk identification, but current prediction methods are insufficient.
This project focuses on developing a new multi-disorder prediction approach that integrates different sources of information. You work with analytical model development, extensive simulation studies and analysis of existing large-scale genetic data.
The project is embedded in the Statistical Genetics Psychiatry Group within the department of Psychiatry at Amsterdam UMC and is funded by the European Research Council (ERC).
As a PhD student, you will contribute to the development of innovative multi-disorder genetic prediction methods in psychiatry. The positions are expected to start in the course of 2026. We are looking to recruit two PhD students for this project.
Your work focuses on integrating multiple sources for prediction, including common and rare genetic variants, family history, ancestry and typical age of onset. Your activities include:
- deriving and extending analytical statistical models;
- conducting large-scale simulation studies;
- analysing real-world genetic datasets;
- applying and extending existing prediction methods developed within the group;
- publishing scientific results and collaborating within a multidisciplinary research team.
You receive dedicated supervision and ample opportunities to further develop these skills.
You predict multiple psychiatric disorders simultaneously, including schizophrenia, bipolar disorder and major depressive disorder. The project builds on previously developed methods such as
DDx-PRS,
BPC and
CC-GWAS.