Maynooth University, National Centre For Geocomputation, Maynooth, Ireland
Deadline: March 6, 2020
The overall aim is to devise innovative Machine Learning (ML) methodologies for mapping, monitoring and predicting soil moisture using Earth Observation (Remote Sensing & In-Situ) inputs. Some of this role will revolve around overseeing the acquisition of optical (RGB, Multispectral, Hyperspectral, Thermal) data from spaceborne (e.g. Copernicus Sentinel1 and Sentinel2), airborne (e.g. drones) platforms as well as in-situ sensors. The main role of this position is dealing with the computational/Machine-Learning aspects; setting up work-flow for labelling Remote Sensing data, building high-quality training data-sets, selecting suitable Machine Learning/Deep Learning models (including Semantic Segmentation), training these models, running predictions and carrying out data quality/verification checks.
- PhD/Master or excellent primary degree with significant Machine Learning expertise/experience
- ability to work independently under minimal direction and on their own initiative