102 machine-learning "https:" "https:" "https:" "https:" "https:" positions in Portugal
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articles based on the results obtained. The goal of this work is to explore and prototype different integration strategies, evaluate their effectiveness in selected machine learning or neuroevolution tasks
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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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fellowship: Novel microfluidics and machine learning tools for unravelling environmental microbiomes Within the remit of the ERA Chair project REACTORS 5.0 “Sustainable REACTOR and microreactor designS
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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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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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implementing data services; developing intuitive and interactive graphical interfaces; integrating 3D visualization tools with a focus on emerging technologies such as AR and VR; applying machine learning-based
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of AI machine/deep learning imagery analysis methodologies and Digital twins applied to cultural heritage assets. 8 - Location Workplace: LNEC – National Laboratory for Civil Engineering, I.P. Avenida do
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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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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