273 algorithm-development-"Newcastle-University"-"Newcastle-University" Fellowship positions in Portugal
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development", project number S1/4.6/E0050, financed by the European Regional Development Fund (ERDF), through the Interreg VI-B Sudoe Programme 2021-2027, under the following conditions: Scientific Area
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call for awarding a part-time (50%) research fellowship (RF) for the development of the platform DB-HERITAGE – Database of construction materials of historical and heritage interest. 3 – Financing source
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and optimisation algorithms, focusing on their practical application in the context of the RaceEngineerAI project. Tasks include: - Developing models capable of simulating the behaviour of racing
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://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Development and testing of algorithms and methodologies based
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 26 days ago
the last mile of maritime container Supply Chain Management, through the analysis, development, and implementation of advanced Artificial Intelligence, optimization, and decision-support algorithms within
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://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Development and testing of algorithms and methodologies based
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recommendation mechanisms based on semantic analysis and natural language processing, with the aim of facilitating collaboration and convergence of proposals. Developing and training NLP algorithms in multiple
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Communications Group: Optical Communication Systems and Networking – AV Work Objectives: 1) Development and implementation of novel digital signal processing (DSP) algorithms, adaptive forward error correction
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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artificial intelligence-based algorithms to optimise operation and predict anomalies in water distribution networks. The algorithms developed should identify patterns and anomalies that indicate the presence