Department : Ncg – National Centre For Geocomputation
Vacancy ID : 005721
Closing Date : 06-Mar-2020

Maynooth University is committed to a strategy in which the primary University goals of excellent research and scholarship and outstanding education are interlinked and equally valued. We are seeking an enthusiastic Data Scientist to join an exciting new research project, SOil MOisture estimates from SATellite based Earth observations (SoMoSAT), for a period of 28 months. The research, which is funded by the Environmental Protection Agency, is seeking to develop a novel data platform to ingest, analyse and fuse multi-thematic and multi-temporal earth observation data streams, including in situ data, using advanced machine learning techniques to derive high spatial resolution soil moisture estimates for Ireland. The successful candidate will be working as part of a project team, alongside Dr. Tim McCarthy and Dr. Rowan Fealy.

The research will directly inform the strategic development of a national monitoring programme and generate a harmonised high resolution soil moisture product to underpin applications in a range of areas, including catchment management, sustainable land use management. The research will also assist in Ireland meeting its international reporting obligations under the United Nations Framework Convention on Climate Change (UNFCCC) through improved land use and soil respiration modelling; it will also inform national policy's in support of the Water Framework Directive and Nitrates Directive.

A suitably qualified candidate (PhD/Master or excellent primary degree with significant Machine Learning expertise/experience) is required to support the data and computational R&D aspects within the SoMoSAT work-programme. 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.

The candidate will work closely with the Principal Investigators and be responsible for ensuring that the data acquisition and computational aspects of the research work plan encompassing spaceborne data collation, drone & In-Situ data acquisition together with Machine Learning workflows are adhered to in terms of tasks, outputs, deliverables and milestones. A high level of initiative and personal drive is required as this will be an environment where you will be joining the project at ground level, helping to lead the design and shape of technical solutions as well as implementing them. The candidate must have the ability to work independently under minimal direction and on their own initiative. Occasionally the work will involve travel in the field, flight testing and meeting with project partners, attend relevant conferences as well as collating/preparing material for research funding calls.

Salary Scale: €38,611 - €42,785 per annum (3 points, starting on point 1)

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

*New entrants to the public sector will be appointed on the first point of the above scale.

Closing Date:

23:30hrs (local Irish time) on Friday, 6th March 2020.

Applications must be submitted by the closing date and time specified. 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.