Postdoc in Climate Modeling
Longin Jan Latecki
We are seeking a Postdoctoral Fellow for an NSF-funded project, "Proto-OKN Theme 1: Knowledge Graph for Climate Model Evaluation and Development." Our goal is to advance climate modeling and weather prediction through innovative Machine Learning and Knowledge Graph (KG) techniques. Information about the NSF program Proto-OKN on https://new.nsf.gov/tip/updates/nsf-invests-first-ever-prototype-open-knowledge-network
In this project, we aim to create a large multimodal KG of the most salient aspects of climate modeling, including data, climate models, and tasks. The climate models include both classical fluid dynamics models as well as AI-based models. The proposed KG will ensure that existing models and datasets are leveraged in new climate modeling undertakings, thereby ensuring that past research investments are reused and fully leveraged in future work.
We are looking to recruit a Postdoctoral Fellow with domain science expertise in climate modeling/weather prediction, and experience related to the Coupled Model Intercomparison Project (CMIP). A track record of working on projects affiliated with the National Oceanic and Atmospheric Administration (NOAA) would be a plus.
Proficiency in programming, particularly in Python and PyTorch, and experience in machine learning, artificial intelligence (AI), and natural language processing (NLP) would be highly advantageous.
Duration: up to 3 years
Location: Temple University, Philadelphia, USA
How to Apply: Please submit the following documents to Eduard Dragut at edr...@temple.edu and Longin Jan Latecki at lat...@temple.edu:
- Curriculum Vitae (CV)
- Brief description of your qualifications and research interests, including a comprehensive list of publications relevant to the project.
- List of two individuals who can be contacted for reference letters.