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UCD Center for Labor and Community - Engaged Research Fellowship Project Coordinator (PROJECT POLICY
analysis and judgment required to clean data, oversee software programming and web development, and coordinate collaborative relationships. Familiarity with rural contexts and northern counties such as
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pilot context. The work plan consists of the following activities: 1) Analysis and specification • Study of the legal domain supported by AI4JURIS and the technologies in use. • Development of priority
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UCD Center for Labor and Community - Engaged Research Fellowship Project Coordinator (PROJECT POLICY
information and applications responsive to those needs. A high level of research analysis and judgment required to clean data, oversee software programming and web development, and coordinate collaborative
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composition and performance. The program concentrates on work that brings cutting edge AI to bear on research in science or music, to advance both the research area and the development of relevant AI methods
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on the development and implementation of advanced systems in cybersecurity, artificial intelligence, and data science in public administration, as well as a scientific capacity-building programme”, within the funding
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Application Deadline 28 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number B-0092-25 Is the Job related to staff position within a Research Infrastructure? No Offer Description
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. Working plan: Objectives and Work Plan: Production of animated educational videos in microbiology Development of laboratory tutorial videos in microbiology/microbiomes Recording, editing, and post
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foods and development of new food ingredients Work Plan: The work aims to develop innovative technological solutions for the valorization of insect fractions, with a particular focus on Tenebrio molitor
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plan: The work consists of developing models for the prediction of biological control agents (BCAs), using different approaches: Machine Learning (random forests, support vector machines, lasso), Deep