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supporting documentation, proven experience in all of the following areas: natural language processing and machine translation (sequence-to-sequence modelling, NMT, glosses); deep learning, Transformers, and
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, etc). The students will work with new approaches to data analysis using Machine Learning and investigate the introduction of agentic workflows and LLM technology into the process. BINDING LEGISLATION
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University of Algarve Research Grant Regulations. (https://files.dre.pt/2s/2021/10/210000000/0013700149.pdf ). Workplace: The work will be carried out on-site, under exclusive dedication, at the Visual
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Programme under Portugal2030 and the European Union, operation code COMPETE2030-FEDER-02975500 (n.º 24829) taking place at the Department of Informatics of the University of Beira Interior(http
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. - Criterion 2: Knowledge in the scientific areas of the project: Academic or applied knowledge in Software Engineering, Intelligent Systems/Machine Learning, and Interactive Technologies. - Criterion 3
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Intelligence (AI) algorithms, including Machine Learning (ML) and Deep Learning (DL) techniques, for advanced signal analysis. The work will focus on developing methodologies for the detection, extraction
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programming in C (on microcontrollers and embedded Linux); ii. Machine learning on the Edge. Priority will be given to candidates enrolled in a Master Program related to Embedded Systems or related fields
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, with applications ranging from scientific research to medical imaging and marketing analysis. With the ever increasing amount of learning data, these algorithms face computational challenges
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learning-assisted computational pipeline for the automated detection of point defects in atomic-resolution scanning transmission electron microscopy (STEM) images. Using monolayer MoS₂ as a model system, the
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. Production of synthesis documents or working papers based on the collected material, suitable for scientific dissemination and to support future editions. Systematisation of the lessons learned and