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with the installation and operation of lab equipment is considered a plus; Familiarity with neuromorphic computing concepts and device modeling is also considered a plus; PhD in Physics, Materials
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for the attribution of 2 grant of Master within the scope of the project of R&D “Intelligent Models for Outpatient and Medical Exams Scheduling Optimization”, FCT 2024.07481.IACDC/2024, supported by
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“Intelligent Models for Outpatient and Medical Exams Scheduling Optimization”, reference FCT 2024.07481.IACDC/2024, financed by measure RE-C05-i08. M04 – "Support the launch of an R&D project programme aimed
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Management; Knowledge of data organization and management; Knowledge of database creation; Good knowledge of quantitative forecasting models and financial markets. Preferred Factors: Experience in creating
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, efficient and practical solutions. In this context we provide efficient computational infrastructure and expertise in process and environmental systems engineering, for model development and assessment in
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reliability analysis, energy yield modelling and integrated sustainable solutions. The Lab has extensive experience in European, National and Industrially funded projects, as coordinator and partner with a
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for managing data related to built heritage, with the aim of integrating advanced information modeling and simulation features in the future, such as 3D visualization, Augmented/Virtual Reality (AR/VR), and
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electronic sensors, fitting it to physiochemical models to understand NP and surface interactions, and perform optimisations for sensing purposes; Perform sample preparation and isolation of NPs; Design and
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data exploration and processing; Knowledge of Generative AI models n mainly LLM's; Knowledge of satisfaction model analysis. Workplan and objectives to be achieved: The work plan aims at the development
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from academic degree recognition processes. Preferred factors: Knowledge of Machine and Deep Learning; Knowledge in data exploration and processing; Knowledge of Generative AI models n mainly LLM's