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or more), which is optional (not compulsory) and the reimbursement corresponds to the 1st step of the contribution base. 9. Evaluation methods: 9.1. The selection methods are as follows: curricular
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Desenvolvimento Regional (FEDER), through the Innovation and Digital Transition Program (COMPETE2030) of Portugal 2030. VII - Selection Methods: Evaluation of the academic record (AR) VII.I - AR - In the evaluation
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) and the reimbursement corresponds to the 1st step of the contribution base. 9. Evaluation methods: 9.1. The selection methods are as follows: curricular assessment (AC – abbreviation in Portuguese) with
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the delivery of proof of enrollment by the time of contracting – see point 2 of Article 10 of the Research Fellowship Regulations No. 950/2019 of FCT – and personal identification elements) *; Experience with
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elements) *. * mandatory requirement Work plan: The candidate will carry out R&D activities within the scope of the HEARTChest project, namely: Support the analysis of consumer preferences and perceptions
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personal identification elements) *. * mandatory requirement Work plan: The candidate will carry out R&D activities within the scope of the HEARTChest project, namely: Support the organization and
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reimbursement corresponds to the 1st step of the contribution base. 9. Evaluation methods: 9.1. The selection methods are as follows: curricular assessment (AC – abbreviation in Portuguese) with a weighting of 60
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) Classification of industrial equipment and fault localization functions, based on methods that are already studied and understood, but not yet computationally optimized or operational in real time; 3) Power
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samples, physical-chemical analysis (pH, ºBrix, acidity, color, among other parameters), quantification of captan and its metabolites, as well as validation of the analytical method. Preparation and conduct
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feature selection methods to pinpoint small sets of neurons that encode concepts within artificial neural network models. Where to apply E-mail jleite@fct.unl.pt Requirements Research FieldComputer science