PhD in seasonal prediction of harmful algae blooms

Nansen Environmental and Remote Sensing Center (NERSC), Bergen, Norway
Closing date: 01 August 2020

The Nansen Center has a vacancy for a Doctoral fellowship (PhD candidate) in the field of climate prediction. The position is an institute-defined PhD topic, which is fully funded by the Research Council of Norway for a three-year period. The candidate will be employed at NERSC and formally complete the doctoral degree at the University of Bergen.

NERSC introduced the Ensemble Kalman Filter (EnKF) data assimilation method in the 1990s and has maintained its further theoretical development and application, including combination of data assimilation with machine learning. The center develop and maintain two state-of-the-art prediction systems: The Earth System seasonal-to-decadal predictions with the Norwegian Climate Prediction Model (NorCPM) and the real-time ocean and sea ice forecasting system for high latitudes within the European Copernicus Marine Environmental Monitoring Services.

The candidate will focus on research for the identification of harmful environmental conditions related to ocean fisheries and aquaculture. The candidate will analyse in-situ, satellite observations and model simulations and explore the use of machine learning techniques to predict the risks of occurrence of harmful algae bloom in Norway at sub-seasonal to seasonal time scales. The prediction scheme will be fed by existing dynamical climate predictions (e.g NorCPM, C3S) and real-time ocean colour satellite data.

The candidate will be supervised by Dr. François Counillon who has expertise on data assimilation and climate prediction and Dr. Julien Brajard who has expertise on machine learning and remote sensing.


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