Department : Computer Science
Vacancy ID : 008402
Closing Date : 17-Jan-2021

The Role

This research project will generate spatial-temporal datasets from sources various Spaceborne Satellites, Drones, in-field instruments, wide area sensor networks as well as ongoing national database compilation programmes. Examples of these datasets include optical (RGB, video, hyperspectral, multispectral, thermal), LiDAR, Navigation, Radar, Flux-tower, Soil-moisture as well as varied land-cover, energy, demographic databases. Some of these datasets will be simple, static, one dimensional datasets, others will be multi-dimensional datasets streaming in near real-time. These multimodal datasets will be stored on a petabyte scale (Microsoft Azure)  cloud platform.

We are seeking an Earth Observation (EO) scientist with solid Remote Sensing expertise in working with various Spaceborne (Optical, Radar) as well as Airborne (Multispectral, Hyperspectral) datasets. Reasonable exposure to EO data handling including sensor calibration, processing (radiometric, geometric), feature selection, contemporary/emerging classification techniques including OBIA & ML modelling, time-series analysis  as well as validation and Data Quality. The EO Scientist will work closely with the Principal Investigators (PIs), Project Manager (PM) and Data Platform Manager to support the various EO R&D activities of wider research team, partners  and collaborators.

Salary

Salary scale Pt 1: €45,942

Increment at 12 months to Pt2 €47,264

Appointment will be made in accordance with the Department of Finance pay guidelines.

Closing Date:

23:30hrs (local Irish time) on Sunday, 17th January 2021.

Applications must be submitted by the closing date and time specified above. Any applications which are still in progress at the closing time on the specified closing date will be cancelled automatically by the system.

Late applications will not be accepted.

Maynooth University is an equal opportunities employer

The position is subject to the Statutes of the University