UCD Post-doctoral Research Fellow Level 1
University College Dublin has secured funding under the Department of Enterprise Trade and Employment’s (DETE) Disruptive Technology Innovation Fund (DTIF) to establish a new Earth Observation platform designed for non- specialist users. The CAMEO (Creating an Architecture for Manipulating Earth Observation data) project seeks to democratise access to an ever-increasing volume of Earth Observation data to develop a sustainable internationally trading Earth Observation services sector in Ireland.
CAMEO will provide a new means of accessing international EO/UAV/Land-based sensor data and mechanisms for combining this with national climate, agriculture, and marine databases to unlock real, tangible potential for Irish industry, the public sector, and research. CAMEO will establish Ireland as an international leader in using EO data for economic and societal benefit.
The members of this project consortium, led by UCD, include Vertice Integration Services Ltd T/A Vertice Cloud, BCC Risk Advisory Ltd T/A Edgescan, The Icon Group Ltd, Treemetrics Ltd, TechWorks Marine Ltd and Dell Technologies.
This is a research-focused role, where you will conduct a specified programme of research supported by research training and development under the supervision and direction of a Principal Investigator.
The primary purpose of the role is to further develop your research skills and competencies, including the processes of publication in peer-reviewed academic publications, the development of funding proposals, the mentorship of graduate students along with the opportunity to develop your skills in research-led teaching.
This position will involve researching and developing tools, protocols and algorithms related to the data quality assessment. Poor quality data will invariably lead to poor decisions. Therefore, it is imperative to seek to ensure that the CAMEO data warehouse is populated with quality data or, at the very least, data for which the indicative quality of data is known. Adjudication of data quality and mechanisms for doing so need to be incorporated throughout the entirety of the big data model, including data collection, data pre-processing, data processing and analytics, and data use.
In addition to the Principal Duties and Responsibilities listed below, the successful candidate will also carry out the following duties specific to this project:
Liaising with stakeholders to define suitable use case demonstrators of EO data and define a framework to evaluate the quality of input data within this use case.
Analysing and comparing EO data sets from multiple sources for known data quality issues.
Application of evidence and research-based approaches to autonomous data quality tagging.
Developing algorithms/models for assessing data suitability for integration into a data warehouse (against
several defined and innovative metrics).
Competition closes: 15th March 2022
Apply Below (Ref: 014222)