Postdoktor inom exposomanalyser
Core
Postdoctoral researcher conducting exposome and metabolomics analyses using advanced statistics and machine learning to study links between biomarkers, environmental factors, and disease outcomes in a clinical setting.
Role type
Postdoctoral researcher (clinical bioinformatics/metabolomics)
Builds
Research findings on disease mechanisms and diagnostic/therapeutic development
Domain
Clinical medicine, metabolomics, exposomics, epidemiology
Deliverable
research
Required skills
Mass spectrometry data preprocessing and quality control, Untargeted mass spectrometry data analysis, Metabolite identification (OpenMS, SIRIUS), Statistical modeling (regression, survival analysis), Programming (R, Python), Scientific writing, Student supervision
Preferred skills
TraceFinder software, Reproducible workflow documentation, Large-scale data management, Survey and EHR data analysis, Advanced statistical methods (G-computation, WQS, Cox models, mediation), Machine learning (GNN, LSTM, Transformers, CNN), Conformal prediction, Explainable AI
Technologies
OpenMS, SIRIUS, TraceFinder, R, Python, GitHub, Docker, Singularity, Nextflow
Responsibilities
Preprocess and quality control high-dimensional mass spectrometry and register data, Perform statistical analyses to study associations between biomarkers, exposures, and disease outcomes, Visualize and interpret results, Document workflows and results, Collaborate on statistical analyses for other group projects, Participate in research meetings and external collaborations
Seniority
Postdoctoral researcher (early-career independent researcher)