Postdoctoral Fellow – Proteomics

About the role

This four‑year postdoctoral fellowship focuses on causal and dynamic modeling of the human plasma proteome to uncover therapeutic targets. The fellow will integrate large‑scale proteomic, genetic, and phenotypic data using advanced statistical and computational methods.

Key responsibilities

• Conduct independent research combining population‑scale proteomics, genomics and phenotype datasets.
• Develop and apply statistical approaches for causal inference, longitudinal analysis and multi‑omic integration.
• Identify disease‑associated proteins, investigate their regulation and prioritize therapeutic candidates.
• Collaborate with multidisciplinary scientists across genetics, bioinformatics, AI and disease biology.

Required profile

• PhD completed in Statistics, Statistical Genetics, Bioinformatics, Computational Biology, Data Science or a related quantitative discipline.
• Strong publication record and experience with large‑scale human biomedical datasets.
• Excellent written and verbal communication skills and ability to work in a collaborative research environment.

Required skills

• Proficiency in R and Python programming.
• Experience with Linux and high‑performance computing environments.
• Knowledge of statistical genetics methods such as GWAS, QTL analysis or Mendelian Randomization.