1 Postdoc (m/f/d) in Causal Inference / Statistics
Core
Develop and apply causal inference methodology for individual-level health intervention effects and treatment effect heterogeneity within digital N-of-1 trials and multimodal biomedical data analysis.
Role type
Postdoctoral researcher in causal inference and statistics
Builds
Methods and software for personalized health recommendations and chronic disease prevention
Domain
Nutrition science, precision medicine, causal inference, deep learning
Deliverable
production ML models | research
Required skills
Causal inference, Statistics, R, Python, Open-source software development
Preferred skills
Deep learning, Multimodal data analysis, N-of-1 trial design
Responsibilities
Develop methodology for individual-level inference on health interventions, Develop best practices for causal inference in N-of-1 trials, Investigate treatment effect heterogeneity, Collaborate on deep learning methods for multimodal data, Implement causal inference methodology on StudyU platform, Create data visualizations and reports for scientific publications and patients
Seniority
Postdoctoral researcher
