Basic Function:

Remote sensing of biodiversity and habitat is well developed at regional and national scale but less attention has been paid at farm scale and at assessing whole farms. New developments in farm scale assessment of biodiversity are being driven by a change in emphasis from compliance to one of impact. The Tailte Éireann National Landcover Map presents a 2018 baseline of land cover for the country and potentially forms a base for assessing biodiversity on the farm. Teagasc are currently exploring new machine learning methods to integrate remote sensing of farm habitats with ground level scoring of farm biodiversity value but many issues still need to be considered.

This Post Doc presents an opportunity to address these fundamental research challenges through original scientific investigation. The objective is to conduct research that advances our understanding of satellite-based biodiversity assessment at farm scale, with particular focus on developing methodologies that can accurately detect and quantify change over time. This work will examine the technologies’ sensitivity to change; tackle the issues around scale and land ownership in farm biodiversity value scoring, and test methods to remotely assess biodiversity attributes in the context of sustainability policy frameworks.

Background:

Irish agricultural is faced with the complicated challenge of meeting global food demand while simultaneously meeting environmental obligations whilst ensuring economic viability of farming.

The objective of the large scale wider project, of which the PostDoc is part, is to develop an accessible, user friendly digital platform that robustly assesses the economic, environmental, and social sustainability of all major farming systems in Ireland, and provide a decision support tool to communicate the benefit of practice adoption. The project builds on a Teagasc, ICBF, and Bord Bia collaboration who together have developed a digital platform AgNav (https://www.agnav.ie/landing ).

The successful candidate will be working with a team of PhD students, post-doctoral researchers, and senior staff in the area of machine learning, earth observation and geo-sciences in the context of the sustainability of Irish and European farming. At the end of the project the candidate will have contributed original research findings to the international scientific community, developed an updated National Land cover Map as a research output, engaged with Irish Farmers through digital co-design methodologies, collaborated with agri-environmental policy makers, and published substantially on Geo-AI methodologies and applications.

The Teagasc post-doctoral programme provides training and development opportunities for early career scientists that enhances their experience of learning, and equips them with the necessary skills for the next stage of their chosen career in research.  Appointees to a Teagasc Post-Doctoral Fellowship will be required to undertake a Level 9 Professional Diploma in Researcher Development delivered by University College Dublin (UCD).

This professional diploma is a flexible, modular programme which embraces a blended learning approach to align with the Post-Doctoral Fellow's role in Teagasc.  It is designed to develop competencies and transferable skills in research, professionalism, communication and career development.  The majority of the programme is delivered online with the remaining elements delivered in-person at Teagasc locations.  This blended approach affords the Post-Doctoral Fellow the opportunity to meet and network with other Teagasc colleagues.  During the course of the diploma Post-Doctoral Fellows will have access to a full range of supports including the UCD library, writing centre and careers centre.

This is a research focused training role, the primary purpose of which is to provide early career scientists with the opportunity to develop their research skills and competencies. The Post-Doctoral Fellow will, while working in conjunction with senior research staff, gain insight and experience into a variety of areas including the processes of project and budgetary management, publishing in peer-reviewed academic journals, writing grant applications, and attracting external funding; the development of active collaboration with relevant national and international research communities; the development of communication and presentation skills, leadership and management skills, and overall career development. Modules will be conducted under the supervision and direction of the Project Leader or other designated manager in conjunction with the Head of Department. 

Gain first-hand insights into the Teagasc Post-Doctoral Fellowship Programme from those who've lived it.  Click here to explore their stories.

Duties & Responsibilities specific to this project:

• Conduct original research on farm-scale biodiversity remote sensing methodologies and lead or support publication of findings in high-impact, peer-reviewed journals.
• Generate a National Landcover Map change product (2018-2024) as a research output and validation dataset.
• Develop and test novel machine learning approaches for integrating satellite data with ground-level biodiversity assessments.
• Investigate the sensitivity and accuracy of remote sensing technologies for detecting biodiversity change at farm scale.
• Research methodological solutions to challenges around scale, land ownership boundaries, and temporal change detection in farm biodiversity assessment.
• Contribute to international scientific conferences and present research findings to academic audiences.
• Engaging with stakeholders in the AgNav co-design process to inform research directions and validate findings.
• Show leadership in advancing Geo-AI research approaches within Teagasc and contribute to grant applications.
• Assist to organise research workshop on "Farm Boundaries" and methodological challenges.

Additional Duties & Responsibilities:

• To interpret research findings and prepare scientific and popular press publications.
• To disseminate research findings to a variety of audiences as appropriate.
• To assist Teagasc in meeting the commitments of the Quality Customer Service Charter and Action Plan.
• To comply with all relevant Teagasc policies and procedures.
• To fully co-operate with the provisions made for ensuring the health, safety and welfare of themselves, fellow staff and non-Teagasc staff and co-operate with management in enabling Teagasc to comply with legal obligations. This includes full compliance with the responsibilities outlined in the Safety Statement.
• To actively participate in the Teagasc Post-Doctoral Fellowship programme and review processes, and to undertake all Post-Doctoral Fellowship training and associated duties as agreed in the Training & Development Plan.
• To take up additional duties as they may arise and be assigned by management.

This section outlines the qualifications, skills, knowledge and/or experience that the successful candidate would be required to demonstrate for successful discharge of the responsibilities of the post.  Applications will be assessed on how well candidates satisfy these criteria.

Essential

• PhD in Earth Observation, Geo-Stats, GIS, Earth Science, or similar
• Relevant research experience not to exceed 3 years’ post-PhD
• Demonstrated research and technical expertise in Machine Learning approaches within GIS, Earth Observation mapping, Coding, Geographic or Climate Analytics or similar
• Evidence of research activity (publications, conference presentations, awards) and future scholarly output (working papers, research proposals etc)
• Excellent project management, analytical, report writing and data analysis skills
• An ability to collaborate with team members and PhD students to help build research knowledge and skill and to guide professional development
• Commitment to teamwork and collaborating with colleagues as per our Teagasc Together ethos
• Excellent communication skills (oral, written, presentation) with an ability to enable effective knowledge and technology transfer
• Ability to generate new ideas, unique concepts, models and solutions

Desirable

• Experience in biodiversity assessment or ecological applications of remote sensing
• Experience in Geo-AI, Digital Delivery, and precision agriculture applications
• Experience in setting own research agenda and developing independent research questions
• Evidence of teamwork and collaboration with relevant academic and industry partners
• Knowledge of agricultural systems and farm-scale environmental challenges

Note:  Alternative location(s) may be considered solely at the discretion of Teagasc management.