Imperial College, London, 17-21 August: Developing analytical skills in Bayesian inference and climate attribution for environmental health applications.
Course description:
This summer school is essential for researchers keen to progress in assessing the health impacts of climate-related hazards. Participants will learn how we can scientifically link climate change to health outcomes using advanced methods from environmental epidemiology and climate attribution science.
It is a three-day workshop aimed at researchers in Environmental and Climate Health who are keen to explore Bayesian modelling for environmental and climate epidemiology.
This summer school is designed for postgraduate students and researchers at any stage in their career who are interested in climate and health attribution and are keen to learn advanced statistical methods.
To participate, you should:
- Be familiar with conda or similar package managers for installing python and R packages
- Be familiar with spatial/temporal data and common distributions (e.g., normal, Poisson) - helpful but not required
- Know the basics of R and RStudio (e.g., installing packages)
- Bring your own laptop
Lecturers:
Fredi Otto, Imperial College London, London, UK
Clair Barnes, Imperial College London, London, UK
Garyfallos Konstantinoudis, Imperial College London, London, UK
Robbie Parks, Columbia University, New York, US
Structure and fees:
There will be two modules that can be attended individually, and rates depend on which modules you undertake and whether you are a PhD student or Postdoctoral Researcher/ Academic.
Find further information and register here.
