DTU Compute
Posted 26th June · Still online 20th July
PhD Scholarship in Causal-Informed Machine Learning Methods for Climate Modelling - DTU Compute
Develops causal-informed machine learning methods to perform multi-seasonal Arctic sea-ice prediction, combining causal analysis, generative models and explainable AI. Works with large climate datasets (CMIP6, ERA5, CERRA2), implements models in Python (PyTorch/Flax) on HPC, and produces probabilistic forecasts and analyses to support early-warning insights for ice-free Arctic summers.
Kgs. Lyngby
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🧪 Science, Research & Academia