72 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" scholarships at Universidade de Coimbra
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developing research in the area of computational learning, generative learning, and computer vision (60%); - Criterion 2 – Motivation and interest (40%). VII.III- The evaluation of the criteria and the final
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the scientific domain of the problem, the scholarship holder is expected to acquire skills in research methods and teamwork. Planned activities: - Study of existing methods and state-of-the-art techniques
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are those approved under the University of Coimbra's Research Grant Regulations Where to apply Website https://apply.uc.pt/ Requirements Research FieldEngineering » Computer engineeringEducation
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; • Organization, systematization, and management of laboratory data. The candidate will also participate in the integration of experimental results with bioinformatics analyses and machine learning methodologies
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while protecting data privacy. Unlike traditional centralized machine learning, where data must be collected and stored in a central server, FL allows multiple parties to collaboratively build a global
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virtual or augmented reality, 3d digitization and rendering, human-computer interaction and user-centered design VII.II- I – In the evaluation of the interview, candidates' performance will be assessed
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on the development of methodologies and techniques of Evolutionary Computation and Machine Learning. V - Initial grant duration: 3 months V.I - Renewal Possibility: Possibily renewable VI - Funding and financial
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the support of the FCT. The publication rules are available on the FCT website, as well as on the websites of the funding Operational Programs, if applicable. The use of the FCT logo available at http
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on the FCT website, as well as on the websites of the funding Operational Programs, if applicable. It is expressly mandatory to use the FCT logo available at http://www.fct.pt/logotipos/ and, when applicable
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' performance will be assessed according to the following weights and criteria: - Criterion 1 - Knowledge in the areas of Bioinformatics, Artificial Intelligence and Machine Learning - Criterion 2 – Motivation