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learning algorithms in non-stationary environments. Specifically, • One of the grantees is expected to investigate/develop scenarios of evaluation involving populations of social-learning agents. In
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held by the grantee. 5 | OBJECTIVES/WORKPLAN The grantee will develop new deep-learning approaches to extract relevant features in large datasets to understand the environment's causal structure
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, resources and services provided through the unique competencies available at the institution. INESC-ID has a strong international academic environment and inclusive work environment. The Executive Board
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environments: Python, PyTorch, Git, CUDA. 8 | EVALUATION CRITERIA AND COMMITTEE The selection will be according to the following criteria: Previous experience: 50% MSc grade: 30% Topic of dissertation: 20