Doktorand i statistik med tillämpningar inom genetik
Core
Developing scalable statistical and computational tools for Genome-Wide Association Studies (GWAS) and polygenic risk score (PRS) prediction to discover heterogeneous genetic effects and predict complex phenotypes.
Role type
PhD researcher in applied statistics (genetics)
Builds
Open-source software tools (R/Python) and statistical methods for genetic discovery
Domain
Statistical genetics / Bioinformatics
Deliverable
production ML models
Required skills
Quantile regression, high-dimensional inference, optimization, stochastic modeling, GWAS analysis, polygenic risk score construction, R, Python
Preferred skills
Mixed models, conformal prediction, ADMM-based optimization
Technologies
R, Python
Responsibilities
Develop scalable quantile regression methods for GWAS in biobank scale; Construct PRS methods providing prediction intervals; Develop computational strategies including screening rules and approximations; Implement user-friendly open-source software.
Seniority
PhD candidate (early career researcher)