UCD Post-doctoral Research Fellow Level 1 # 015046
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- UCD Post-doctoral Research Fellow Level 2 Competition # 017045
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- UCD Research Fellow # 016241
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- UCD Post-doctoral Research Fellow Level 1 # 015822
- UCD Post-doctoral Research Fellow Level 2 # 015822
- UCD Post-doctoral Research Fellow Level 1 # 015836
- UCD Post-doctoral Research Fellow Level 1 # 015534
- Centre Manager # 015683
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- Lecturer/Assistant Professor in Computer Science # 015571
- Lecturer/Assistant Professor in Computer Science (with expertise in Digital Forensics / Cybersecurity) # 015580
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- Senior Data Scientist # 015546
- Senior Research Data Scientist # 015543
- UCD Post-doctoral Research Fellow Level 1 # 015534
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- Research Scientist, UCD School of Computer Science
- Post doctoral Research Fellow Level 1 or Level 2, UCD School of Computer Science
- Research Fellow, UCD School of Computer Science
- Research Assistant
- UCD Post-doctoral Research Fellow Level 1
- UCD Post doctoral Research Fellow Level 2
- Lecturer | Assistant Professor in Computer Science, UCDCS
- BDIC Lecturer/Assistant Professor in Computer Science, UCD School of Computer Science
- Research Assistant, UCD School of Computer Science, Temporary 18 month post
- Applicants are invited to apply for a Post-doctoral Researcher – Level 1 & 2
- Lecturer/Assistant Professor in Computer Science, UCD School of Computer Science
- UCD Post-doctoral Researcher (Level 1) x2
UCD Post-doctoral Research Fellow Level 1
Position Summary
CAMEO
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, researchers. 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 competences, 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.
Earth Observation (EO) data embraces a myriad of potential data sources and streams, including but not limited to satellite, drone, lidar, ground segment, and citizen derived. The CAMEO EO platform will make provision for such diverse and rich datasets through functionality for storage and access; cataloguing and searching; data processing and analysis; visualisation; etc. The Postdoctoral scientist will be part of a large multidisciplinary team. They will collaborate with industry to develop demonstrators for agriculture/climate applications.
In addition to the Principal Duties and Responsibilities listed below, the successful candidate will also carry out the following duties specific to this project:
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Liaising with stakeholders to identify recurrent and generic sector needs, as well as selecting regions for analysis to define suitable use case demonstrators of EO data in the areas of agriculture/climate.
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Contributing to the design and delivery of the CAMEO EO software system.
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Using EO data to demonstrate CAMEO infrastructural support and capacity across distinct problems.
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Applying machine learning to develop and test new methods of external validation of EO data for agriculture/climate applications.
Competition closes: 06th October 2022
Apply Below (Ref: 015046)