Tuomas Kilpeläinen

Postdoc opportunity in computational genomics , statistical genetics , and cardiometabolic GWAS at the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR), University of Copenhagen . The project, based in the Kilpeläinen Group , focuses on improving scalability and statistical power for genetic discovery under pervasive phenotype missingness in biobank-scale studies. The work centers on phenotype prediction and imputation, uncertainty-aware inference, and robust modeling approaches that can support large international biobank analyses. A further theme is the use of large-scale proteomics as a cross-cohort predictor layer, especially where clinical predictors differ across studies. The postdoc will evaluate and integrate modern methods for genetic association studies under complex data conditions, including heterogeneity by age, sex, adiposity, or inflammatory state. The role may include methodological development, simulation and benchmarking, cross-cohort validation, and large-scale data analysis using multi-cohort datasets. Eligibility highlights: applicants should have a PhD (or be near completion) in bioinformatics, statistical genetics, computational biology, biostatistics, data science, epidemiology, or a related quantitative/life-science field. Strong skills in statistical modeling, machine learning, GWAS, imputation, programming (Python/R), and reproducible research are expected. The program is open to applicants with a PhD from outside Denmark, and to certain Danish PhD holders with documented research experience outside Denmark. Funding and terms: full-time postdoc for 2 years. Salary, pension, and employment conditions follow Danish university agreements; a supplement may be negotiated. The position is part of the CBMR International PhD & Postdoc Program. Deadline: 2026-08-10. Apply online in English and upload the required documents before the deadline.