News

Call for admission to the PhD Courses 2026/27 (Cycle XLII)

Call opening: (Page under update. The selection notice will be published soon)
Call deadline: (Page under update. The selection notice will be published soon)

The new call:

The summary information on the LERH specific call:

  • In English (Page under update. The selection notice will be published soon)
  • and Italian (Page under update. The selection notice will be published soon)

For the Research topics see here.

Here is the format for the Curriculum vitae et studiorum that has to be filled and presented for this Call (year 2026, XLII Cycle)

Here is the format for the Research project template that has to be filled and presented for this Call (year 2026, XLII Cycle)

Two PhD positions are available for the MSCA Joint Doctorate (JD) project “GreenFieldData - IoRT Data Management and Analysis for Sustainable Agriculture” funded by the European Commission, with Professor Marinello as scientific supervisor for Unipd

PhD-E: "Optimizing Images Quality and Deep Learning Methods for Vineyard Disease Detection", Joint degree with University of Padua and Poznan University of Technology - PUT.

Description: Viticulture is one of the most valuable agricultural sectors in Europe, but it faces increasing challenges from plant diseases that threaten both yield and quality. Early and reliable detection of vineyard diseases is crucial for ensuring sustainable production, reducing economic losses, and minimizing the use of chemical treatments. Current monitoring methods are often manual, time-consuming, and prone to inconsistencies, which limits their scalability and effectiveness. Recent advances in robotics, imaging technologies, and artificial intelligence offer transformative opportunities for vineyard disease detection.

PhD-P: " Agricultural AI data integration and management based on LLM", Joint degree with University of Padua and Université Toulouse Capitole - IRIT.

Description: Agriculture and agronomy generate a wide variety of data (connected equipment, weather, environmental sensors, livestock, crop monitoring, etc.). Despite a lot of progress, the value of this large quantity of data remains complex to develop, often not well automatized and underexploited. This data suffers from a strong disparate and disseminated nature (heterogeneity). This research will produce a systematic classification of different alternative scenarios and will investigate best approaches allowing an efficient and effective combination and integration of heterogeneous data.

The information sheet and link to apply are available on the page: https://www.eu4greenfielddata.eu/phd-positions-application/list-of-phds

Application deadline: April 15, 2026