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architectures for explainable dual-process computation Design and development of deep neural network architectures and algorithms for the implementation of dual process computation approaches that improve
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to their classification consisting on the sum of the partial classifications assigned in each evaluation criterion, and considering the weighting factor given to each parameter. In this process abstentions are not allowed
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to their classification consisting on the sum of the partial classifications assigned in each evaluation criterion, and considering the weighting factor given to each parameter. In this process abstentions are not allowed
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among partners Plan, organize and monitor the project activities, milestones, deliverables and periodic reports Manage the internal review process for project deliverables to ensure quality and
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given to each parameter. In this process abstentions are not allowed. In the event of a tie among candidates with the same highest evaluation score, the Evaluation Panel reserves the right to conduct
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to their classification consisting of the sum of the partial classifications assigned in each evaluation criterion, and considering the weighting factor given to each parameter. In this process abstentions are not allowed
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this process abstentions are not allowed. In the event of a tie among candidates with the same highest evaluation score, the Evaluation Panel reserves the right to conduct interviews to have a more objective
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this process abstentions are not allowed. In the event of a tie among candidates with the same highest evaluation score, the Evaluation Panel reserves the right to conduct interviews to have a more objective
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factor given to each parameter. In this process abstentions are not allowed. In the event of a tie among candidates with the same highest evaluation score, the Evaluation Panel reserves the right
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according to their classification consisting on the sum of the partial classifications assigned in each evaluation criterion, and considering the weighting factor given to each parameter. In this process