Doctoral studentship in Statistics with applications to genetics

Lund University School of Economics and Management, Department of Statistics, Lund, Sweden invites applications for Doctoral studentship in Statistics with applications to genetics. The doctoral student will work on the research project entitled “Quantile Regression Models for Genetic Discovery and Phenotype Prediction”. The project aims to develop scalable statistical and computational tools for modern genome-wide association studies (GWAS) and polygenic risk score (PRS) prediction. The overall aim is to move beyond standard mean-based models and develop quantile-regression methods that can detect heterogeneous genetic effects and predict the full conditional distribution of complex phenotypes. The project combines theoretical statistics, high-dimensional inference, optimization, and large-scale computing with applications in statistical genetics. The doctoral student is expected to contribute to one or more of the following themes: • developing scalable quantile regression methods for biobank scale GWAS with population structure and/or related individuals • constructing quantile-regression-based PRS methods that provide prediction intervals and tail-probability risk summaries • developing computational strategies such as screening rules, ADMM-based optimization, mixed-model approximations, and conformalized prediction intervals • implementing user-friendly software, preferably as open-source tools in R and/or Python. For more details see: https://stat-lu.github.io/PhdPos_2026/ The employment as a PhD student is granted on yearly basis and the total period of employment may not exceed 4 years of full-time studies. Departmental duties, i.e. teaching, administration or research not directly connected to the dissertation topic, may amount to a maximum of 20% of full time. When such departmental duties are performed, the length of employment is extended accordingly. Learn more and apply at:

Last updated: 22 May 2026