(M/F) (PhD position) Conversational AI for Sustainable Agriculture: Natural Language Interfaces over Robotic and Analytical Farming Systems

Descrizione

(M/F) (PhD position) Conversational AI for Sustainable Agriculture: Natural Language Interfaces over Robotic and Analytical Farming Systems Sintesi in italiano (traduzione automatica): L'organizzazione offre una posizione di dottorato in Intelligenza Artificiale Conversazionale per l'Agricoltura Sostenibile, con sede presso l'Università Claude Bernard di Lione e l'Università di Milano. Il progetto di ricerca, della durata di 36 mesi, si concentra sulla creazione di interfacce conversazionali per facilitare l'interazione tra agricoltori e robot agricoli. Le principali mansioni includono la progettazione di soluzioni conversazionali, la validazione di prototipi e l'analisi di dati provenienti da sistemi IoT e robotica agricola. È richiesta una laurea in Informatica, Matematica o un campo correlato. Il candidato ideale avrà competenze in modelli di linguaggio, elaborazione del linguaggio naturale e sistemi di navigazione autonoma, contribuendo a rendere l'agricoltura più sostenibile e accessibile anche a utenti non esperti. Co-tutelle - University Claude Bernard Lyon 1, Doctoral School Informatics and Mathematics, Lyon, France (18 Months), Supervisor: G. Vargas-Solar Laboratory LIRIS, CNRS, France - University of Milan, Dept. of Agricultural and Environmental Sciences - Production, Landscape, Agroenergy, Italy (18 Months), Supervisor: R. Oberti Secondments: - ProBayes, Grenoble, France (Mohamad Othman Abdallah) months 1 month, conversational solutions and validation tests of experimental results related to developed prototypes. Designing conversational solutions and for the assessment of conversational solutions after having worked on LLM's. - ISOL, M. Penco, 24th Month, 4 months, working with autonomous navigation system with the aim of simplifying the interaction between farmers (or non-expert users) and agri-robots for programming field missions. Agricultural robots, drones, IoT sensors, and smart farming platforms are transforming crop production by improving efficiency, reducing labour, and supporting more sustainable practices. However, these technologies generate large volumes of heterogeneous data and often require advanced technical expertise to operate, configure, and interpret. This PhD project will explore how Large Language Models, Natural Language Processing, stream analytics, IoT infrastructures, and agricultural robotics can be combined to create human-in-the-loop conversational interfaces for smart agriculture. The goal is to allow farmers, agronomists, technicians, and researchers to command robots, query data, monitor operations, and receive explanations through natural language or voice-based interaction. The research will focus on translating user requests into dataflows, API calls, analytics workflows, and robotic actions across distributed IoT, drone, and agri-robot ecosystems. It will address challenges such as semantic grounding, multimodal data interpretation, real-time stream processing, adaptive robot control, trust calibration, and edge-cloud deployment. The expected outcome is an inclusive, interpretable, and sustainable AI-based architecture that makes advanced agricultural robotics and data analytics accessible to non-expert users while supporting more precise, accountable, and environmentally responsible farming. Annuncio in inglese. Fonte: Euraxess (Commissione europea).