Post-doc: Strengthening scientific knowledge on climate and environmental science by using Artificial Intelligence and Machine Learning tools (Environmental Intelligence for Global Change Lab)
This post is part of the emerging interest in strengthening scientific knowledge on climate and environmental science by using Artificial Intelligence and Machine Learning tools for processing big observational/simulated datasets.
The research will focus on:
- Developing AI and ML algorithms for supporting the detection of spatial and temporal patterns and evolutions of climatological fields (e.g., temperature) associated with extreme events (e.g., heatwaves, tropical cyclones).
- Validating the detected teleconnections with data-driven causal inference methods.
- Advancing existing water management solutions by using the newly developed information about extreme event occurrence.
Qualifications for this position include a Ph.D. in computer and/or automation engineering, artificial intelligence, applied mathematics or related fields. Alternatively, candidates having a background in water resources engineering, or a related field of environmental engineering also encouraged to apply. Strong numerical and computational skills are required as well as English language skills both in oral and written communication.
The application package must include CV, list of publications, and the name of two references. Deadline for the package submission: 2 September 2020.