GreenFieldData Project Double Degree PhD Scholarship "Assessing drought effects gr

First Stage Researcher (R1) (Up to the point of PhD)

Horizon Europe - MSCA

Outline

Green Field Data  proposes a high-level interdisciplinary, inter-sectoral and international (triple ‘i’) research project and training network on new IoRT (Internet of Robotic Things) based solutions for sustainable agriculture. Green Field Data  will mobilize 14 Doctoral Candidates enrolled in Double Degree Doctorate programmes with 12 academic main beneficiary partners, across 7 EU countries.

Grasslands cover 39% of Europe’s utilised agricultural area and store over 30% of the global stock of carbon, making them vital for climate regulation, biodiversity, and agricultural productivity. However, they are highly vulnerable to drought, with impacts on ecosystem health, carbon storage, and food production. This PhD project addresses the challenge by integrating Internet of Things (IoT)-enabled visual sensing technologies with advanced data analytics to detect and quantify drought effects on grasslands.

IoT visual sensors, combined with machine learning, offer the possibility to monitor plant health and environmental conditions in near real-time, producing fine-grained spatial and temporal insights. These tools can identify early-warning signals of drought stress and provide actionable recommendations for adaptive management. In addition to its scientific contributions, this work aligns with EU strategic priorities, including the European Green Deal, the Digital EU Programme, and the Climate Adaptation Strategy.

The project’s results will inform evidence-based policies, guide land managers in sustainable practices, and contribute to climate resilience in the agricultural sector—bridging the gap between digital innovation and ecological stewardship.

Months 1-6 Poland:
1) Months 1-3: state of the art of the PhD work – grassland responses to drought and methodologies to phenotype in the field, and define robust sensor-based indicators for the impacts of drought on grassland health and productivity.
2) Months 3-6: choice and order cameras (multispectral, RGB...); acquire knowledge on plant ecophysiology (leaf gas exchange, leaf and soil water status); first analysis of available field data set (species composition, leaf traits, biomass, quality, soil data).

Months 7-24 France:
3) Months 7-9: setup of cameras and ecophysiological plant material in the field to study spatial and temporal insights into grassland ecosystem responses to different drought intensities, enabling early-warning signal identification measure vegetation traits and record images;
Secondment at Sherpa (France) - 1 month - training on embedded artificial intelligence and sensor design.
4) Months 9-12: continue field measurements with cameras and analyse data with predictive models using real-time sensor data and effective ML for grassland drought stress forecasting;
Secondment - 1 month in the Sidam organisation - field-based assessment of drought impacts on grassland in the Massif Central region (France) - agricultural feasibility study exploring technology adaptation, stakeholder engagement, and sustainable monitoring strategies.
5) Months 13-24:
Identification of essential components for a robust framework integrating real-time visual sensor data and historical climate patterns to monitor grassland resilience and inform adaptive management; continue to record images and measure vegetation traits.

Months 25-36 Poland:
6) Months 25-30:
Analyse data and use of sensor-driven models to quantify…