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paper, including the previous developments, should be published and our group established as one of the players in the area of deep-learning for computational mechanics. Legislation and Regulations
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behavior of these components will be developed based on Finite Element Methods (FEM) complemented by Machine Learning models. Legislation and Regulations: Statute of Scientific Research Fellow, approved by
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scientific publication and writing articles in international journals; 8) Experience in data visualization tools and advanced statistical analysis (e.g., pandas, scikit-learn, matplotlib, seaborn, SHAP
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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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interaction with the road infrastructure. • Experience in big data analysis and handling of large data sets, with skills in applying AI and machine learning techniques to traffic pattern analysis and road
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factors: Previous experience in the construction industry; Previous experience in Building Information Modelling; Previous experience in AI and machine learning; Previous experience in process and facility
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at https://www.euraxess.pt at and on the website of the Universidade do Algarve, at https://www.ualg.pt/procedimentos-concursais . Applicable legislation: Decree-Law 57/2016 of 29 August, amended by Law 57
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and written language proficiency in both English and Portuguese (with reference to the context where the candidate learned and perfected both languages or to whether they are native speakers); Detailed
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Neuroscience on object representation and object properties using machine learning and multivariate techniques to analyze the data; support in writing scientific outputs. The grantee will also support the entire
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, and clustering methods; Knowledge of machine learning approaches for classification and patient stratification is valued; Postdoctoral experience in the appropriate field, with research outputs ideally