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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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                to Improve Care and Optimize Resources for Frequent Emergency Users”, (ref.ª 2024.07543.IACDC, financed by "RE-C05-i08.m04 – "Support the launch of a program of R&D projects aimed at the development and 
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                symbolic language. This foundation supports a novel alignment algorithm that quantifies inconsistencies, offers actionable compliance scores, and exposes bottlenecks across control-flow, data, and resource 
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                ) Proficiency in scientific programming tools and development of machine learning algorithms applied to biomedical data (preferably Python and MATLAB); e) Skills in managing computer equipment for advanced 
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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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                -FCT, they are developed in association or cooperation between the higher education institution and one or more R&D units. I.III - Ineligible candidates: Candidates enrolled in non-degree-granting 
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                carry out work within the scope of the OHCare research project, focusing on the development of models and algorithms, their implementation, computational execution and testing, and their application 
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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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                internationally. Main Responsibilities · Contribute to the installation, calibration, and validation of radio monitoring equipment. · Develop and test real-time data pipelines and deep learning algorithms for Solar 
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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