Job Opportunity -Post-Doctoral Researcher or Data Scientist - Maynooth University

[Molly]

Application Closing Date: 23:30 hrs (local Irish time), Sunday, 1 November 2020 Please note all applications must be made via our Online Recruitment Portal at the following link: https://www.maynoothuniversity.ie/human-resources/vacancies

See the attachment for the full job description. 

The Role:
 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 Post-Doctoral Researcher/Data Scientist to join an exciting new research project, SOil MOisture estimates from SATellite based Earth observations (SoMoSAT), for a period of 21 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 Tim McCarthy and Rowan Fealy, and project partners in Teagasc, Reamonn Fealy, Lilian O’Sullivan and Per-Erik Mellander. 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 or highly qualified Masters/or excellent primary degree with significant water / land surface modelling expertise/experience) is required to support the data and computational R&D aspects within the SoMoSAT work-programme. The overall aim is to develop and/or undertake surface based monitoring & modelling to support mapping, monitoring and predicting soil moisture using Earth Observation (Remote Sensing & In-Situ) inputs. Part of this role will involve overseeing the acquisition of relevant geo-spatial (e.g. climate, soils, vegetation) data, including data from spaceborne (e.g. Copernicus Sentinel1 and Sentinel2) and airborne (e.g. drones) platforms as well as in-situ sensors. The main role will involve the development and application of modelling approaches to develop high resolution soil moisture estimates for Ireland. A secondary component will involve the identification of suitable monitoring locations to inform a national monitoring policy. The Post Ref: 007481 2 candidate will work very closely with the existing Data Scientist, who is developing Machine Learning approaches to estimate soil moisture from satellite and drone-based platforms. The candidate will also work closely with the Principal Investigators, and project partners in Teagasc, and be responsible for ensuring that the data acquisition and monitoring and modelling aspects of the research work plan 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. The work will involve travel in the field and meeting with project partners, attend relevant conferences as well as collating/preparing material for research funding calls. Principle duties  Working with the Principal Investigators, existing Data Scientist and wider research team to oversee the collation of all relevant geo-spatial and in-situ data  Evaluate, develop/apply suitable (water balance / land surface) modelling approaches, along with the satellite based information, to derive estimates of soil moisture at high spatial resolution  Undertake evaluation of model and/or satellite derived estimates of soil moisture  Identify a monitoring framework to inform the development of a national monitoring strategy  Lead the publication of papers from the research in international journals  Support the PI in monitoring progress and ensure project work-plan, tasks, deliverables together with key milestones are adhered to.  Attend project meeting with research and funding partners. Support publications and conference presentations.