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other national and international partners. The PhD project is focused on quantifying the role of blowing snow in driving accumulation and sublimation in mountainous conditions. The simulation of blowing
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simulations) to propose solutions. The Research Fellow will be responsible to study through modelling the resilience of the solutions using climate change weather data. Close collaboration with all project
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of blowing snow in driving accumulation and sublimation in mountainous conditions. The simulation of blowing snow in local and regional climate models is poorly constrained, leading to uncertainties in
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allocation and thermal management to achieve optimal performance (iii) Model-in-the-Loop (MIL) validation to simulate components and connected systems to predict thermal behaviour and system
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10.54499/2022.08738.PTDC (https://doi.org/10.54499/2022.08738.PTDC ) funded by national funds (PIDDAC) through FCT/MCTES, under the following conditions: Scientific Area: Chemical Engineering. Admission
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architecture design, simulations, and publicly available genomic datasets to develop new inference methods. The Postdoctoral Associate will conduct research related to creating or testing deep learning models
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depletion, atmosphere circulation, extreme precipitation, ITCZ shift, tropical drying, etc Analyse and interpret research findings and results Work together with modellers and teams in Edinburgh and CICERO
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Programa de Financiamento Plurianual de Centros Académicos Clínicos – CAC 2023-2025 pela Fundação para a Ciência e Tecnologia (FCT) with the following conditions: Research Field: Biomedicine Admission
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. The candidate will apply (glacier-)hydrological models to simulate glacier-/snow- mass balance, runoff and extreme events from the past centuries (~1500) to the end of this century, using bias-corrected and
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wastewater treatment plants, with the following main objectives: 1 - Model calibration through Machine Learning methodologies using process data. 2 - Development of a multimodal online sustainability