50 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" scholarships in Portugal
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- Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID
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- Instituto de Telecomunicações
- Universidade de Coimbra
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of this project for a one-year period (100% full-time commitment) to make a significant contribution to the implementation of machine learning (ML) algorithms. The postdoc is expected to have proven experience in
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Analysis and Decision Support - Applying statistical and machine learning methods to interpret the data, identify trends for optimizing aquaculture conditions.; • Experimental Validation - Conducting
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Python for scientific computing – experience with data analysis and basic signal processing – foundations in machine learning and interest in developing advanced AI models – familiarity with Linux
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of the state of the art in machine learning for generation of artificial data; - identify and select the appropriate methods for the study in question; - develop the research capacity through the application
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
skills. Have very good knowledge of machine-learning and data science methods, especially for timeseries data Have very good programming skills in programming languages such as Python. Have previous
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the European Research Council - ERC COG 101088763. The work for this position is in the area of Machine Learning and Natural Language Processing. We are offering We offer a challenging position with the
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of the Grant are:; 1) To apply machine learning algorithms for the diagnosis of faults and malfunctions in photovoltaic plants, using data from SCADA systems combined with synthetic data from digital twins (DT
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river valleys); • Identify stylistic patterns and regional variations in schematic rock art; • Apply machine learning tools for large-scale stylistic classification; • Establish a robust chronological
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2022.09373.PTDC financed by national funds through FCT/MECI, under the following conditions: Scientific Area: Machine Learning/Recommender Systems Admission requirements: Candidates who cumulatively meet the
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using machine learning; Interpretation of soil profiles and moisture maps. Development and validation of digital tools: Support in building georeferenced web interfaces for data visualization