Postdoctoral Researcher (f/m/x) – Computational Modelling
Core
Develop generative models and simulation frameworks for longitudinal digital phenotyping data to model resilience dynamics and transitions in mental health.
Role type
Postdoctoral Researcher (Computational Modelling)
Builds
Hybrid in-silico framework for synthetic patient trajectories and virtual perturbation scenarios
Domain
Digital Mental Health, Psychiatry, Computational Modelling
Deliverable
production ML models
Required skills
generative modelling, deep learning, time-series modelling, probabilistic modelling, simulation, Python, PyTorch, longitudinal data analysis
Preferred skills
machine learning, dynamic systems theory, open-science practices
Technologies
Python, PyTorch, ecological momentary assessment, actigraphy, GPS-derived mobility measures
Responsibilities
Develop and evaluate generative models for longitudinal digital phenotyping data; Build and refine a simulation framework for synthetic patient trajectories; Design and analyse virtual perturbation scenarios; Develop and validate resilience metrics and approaches for transition typing; Contribute to the implementation of a research prototype and reusable open resources; Support the supervision of junior researchers
Seniority
Postdoctoral, independent researcher with mentorship duties
