UCD Post-doctoral Research Fellow Level 2
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 EMC Information Systems International.
This is an advanced research focused role, building on your prior experience as a post-doctoral fellow, where you will conduct a specified programme of research supported by research training under the supervision and direction of a Principal Investigator.
The primary purpose of the role is to develop new or advanced research skills and competences, on the processes of publication in peer-reviewed academic publications and scholarly dissemination, the development of funding proposals, and the supervision and mentorship of graduate students along with the opportunity to develop your skills in research led teaching.
There is an increasing awareness of the potential of machine learning and AI applied to EO and spatiotemporal data, both in terms of novel insights that can be derived from these data as well as opportunities for developing more capable tools and techniques for accessing, manipulating and processing EO data. This position will involve researching and developing novel tools, techniques and algorithms to support the discovery, selection, fusion, manipulation and analysis of EO and spatiotemporal data with a particular emphasis on the use of machine learning and AI techniques.
In addition to the Principal Duties and Responsibilities listed below, the successful candidate will also carry out the following duties specific to this project:
Developing novel tools and techniques to support the discovery, selection, fusion, manipulation, processing and analysis of EO and geospatial data, particularly leveraging AI and machine learning based approaches
Contributing to the implementation and integration of developed approaches within a cloud-based microservices architecture
Liaising with stakeholders to define suitable use case demonstrators of EO data, and to identify relevant opportunities for machine learning and advanced analytics based solutions. Assist in the implementation of identified machine learning and/or analytics based solutions
Collaborating with work package leaders across the project to harmonise use of machine learning and AI techniques and technologies
Competition closes: 16th March 2022
Apply Below (Ref: 014232)