Digital Twin Development and Data-Driven Algorithms for Plant Health Estimation in EcoSentinel Systems
Pubblicato il 12-10-2026 - Italian Ministry of Education, University and Research in Italia
Organisation/Company Università di Trento Research Field Engineering Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 28 Oct 2026 - 12:00 (UTC) Country Italy Type of Contract To be defined Job Status Not Applicable Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
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Offer Description
This research activity, carried out within the European EcoSentinel project, focuses on the definition and implementation of a Plant Digital Twin dedicated to monitoring and diagnosing plant health.
The candidate will develop data-driven models and machine learning algorithms capable of integrating and processing heterogeneous signals generated by the EcoSentinel platform. Specifically, the research involves analyzing inter-plant communication metrics (such as received signal strength / RSSI and transmission parameters) alongside energy harvesting data from microbial soil processes, aiming to infer plant health indicators (good, warning, danger states) and environmental soil conditions.
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- AFRICA
- EUROPE
- OCEANIA
- NORTH AMERICA
- SOUTH AMERICA
- ASIA
- OTHER
- E. xysqume U.
- CHINA (MAINLAND)
- CHINA (HONG KONG)
Eligibility of fellows: country/ies of residence:
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- AFRICA
- EUROPE
- OCEANIA
- NORTH AMERICA
- SOUTH AMERICA
- ASIA
- OTHER
- E.U.
- CHINA (MAINLAND)
- CHINA (HONG KONG)