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Università di Pisa - Dipartimento di Scienze Agrarie, Alimentari e Agro-Ambientali | Italy | 14 days ago
10 Apr 2026 Job Information Organisation/Company Università di Pisa - Dipartimento di Scienze Agrarie, Alimentari e Agro-Ambientali Research Field Agricultural sciences Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher...
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are united in our efforts to understand, explain and improve our world and the human condition. Description of the workplace Automatic Control is one of the departments at the Faculty of Engineering (LTH
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activity is aimed at developing tools based on machine learning techniques for the automatic analysis of privacy policy pages. CUP: B83C24003210001 Where to apply Website https://xup.di.uniroma1.it
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-technologies ) group, coordinated by Arianna Traviglia. This group focuses on Cultural Heritage Technologies: Automatic Document Analysis. Your activity will comprise State-of-the-art models report preparation
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. The researcher’s activities are to develop and validate on a pilot an agent-based generative-AI pipeline for automatically generating reports from the data collected in the data lake, while supporting and
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for the automatic analysis of vocal and conversational content, with a particular focus on healthcare applications and natural language understanding. The activities will involve the study, design, and validation
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14 Mar 2026 Job Information Organisation/Company Lunds universitet Department Lund University, LTH, Department of Automatic Control Research Field Engineering Researcher Profile Established
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Automatic Object and Behaviour Recognition in Video/ Image Sequences School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Lyudmila Mihaylova Application Deadline
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are united in our efforts to understand, explain and improve our world and the human condition. Department of Automatic Control at Lund University, Faculty of Engineering invites applications for a position as
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Automatization and Digital Enhancement of Characterisation Techniques: Joining the Dots between AI, Machine Learning and Materials Advances School of Chemical, Materials and Biological Engineering