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- Centro de Estudos Filosóficos e Humanísticos (CEFH) | Universidade Católica Portuguesa
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months to two years, or per longer period. 1. OBJECTIVES | FUNCTIONS Development of techniques aimed at enhancing the efficiency of complex ML pipelines, with emphasis on methods aimed at predicting
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development of the Digital Twin, integrating data from industrial welding processes through instrumentation and digitalization for predictive capacity, focusing on interoperability and security within a smart
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Centro de Estudos Filosóficos e Humanísticos (CEFH) | Universidade Católica Portuguesa | Portugal | 12 days ago
as a junior researcher under an uncertain term contract (contrato a termo incerto), predicted to start on December 1, 2025 with the estimate duration of 26 months (duration of the activities) which
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that allow predicting the fermentation conditions to be adopted, based on the nutritional composition of the side streams. Shelf-life determination. Activity 2: Dissemination and communication of the results
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shall be hired by Universidade Católica Portuguesa as a junior researcher under an uncertain term contract (contrato a termo incerto), predicted to start on December 1, 2025 with the estimate duration
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shall be hired by Universidade Católica Portuguesa as a junior researcher under an uncertain term contract (contrato a termo incerto), predicted to start on December 1, 2025 with the estimate duration
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shall be hired by Universidade Católica Portuguesa as a junior researcher under an uncertain term contract (contrato a termo incerto), predicted to start on December 1, 2025 with the estimate duration
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with subsection a), section 1, article 15 from Law nr 57/2017, 19th July, and with the 3rd remuneration position at initial level predicted in article 2 of Regulatory Decree nr 11-A/2017, of 29th
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uncertain term contract (contrato a termo incerto), predicted to start on November 1, 2025 with the estimate duration of 36 months (duration of the activities) which will never, under any circumstances, be
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of Water Supply Systems, through a Smart Predictive Digital Twin and integration of AI for hydraulic modelling, real-time data analysis for advanced loss detection and system optimisation, reducing energy