Digital Twin Development and Data-Driven Algorithms for Plant Health Estimation in EcoSentinel Systems
1 giorno fa
Aosta, Valle d'Aosta, Italia
Italian Ministry of Education, University and Research
Tempo pieno
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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 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.
* AFRICA
* EUROPE
* OCEANIA
* NORTH AMERICA
* SOUTH AMERICA
* ASIA
* OTHER
* E.
U.
* CHINA (MAINLAND)
* CHINA (HONG KONG) Eligibility of fellows: country/ies of residence:
* AFRICA
* EUROPE
* OCEANIA
* NORTH AMERICA
* SOUTH AMERICA
* ASIA
* OTHER
* E.
U.
* CHINA (MAINLAND)
* CHINA (HONG KONG) #J-18808-Ljbffr
- 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 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.
* AFRICA
* EUROPE
* OCEANIA
* NORTH AMERICA
* SOUTH AMERICA
* ASIA
* OTHER
* E.
U.
* CHINA (MAINLAND)
* CHINA (HONG KONG) Eligibility of fellows: country/ies of residence:
* AFRICA
* EUROPE
* OCEANIA
* NORTH AMERICA
* SOUTH AMERICA
* ASIA
* OTHER
* E.
U.
* CHINA (MAINLAND)
* CHINA (HONG KONG) #J-18808-Ljbffr
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Plant Digital Twin Scientist: Data-Driven Health
1 giorno fa
Aosta, Valle d'Aosta, Italia Italian Ministry of Education, University and Research Tempo pienoUniversità di Trento is seeking a researcher to contribute to the European EcoSentinel project by defining and implementing a Plant Digital Twin for monitoring and diagnosing plant health. The role focuses on developing data-driven models and machine learning algorithms that integrate heterogeneous signals from the EcoSentinel platform. You will analyze...