24 algorithm-"DIFFER"-"NTNU---Norwegian-University-of-Science-and-Technology" positions in Portugal
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 11 days ago
to the activities to be developed in Portugal, with a particular focus on the port’s demonstrator. More precisely: Development of forecasting algorithms for different related variables, e.g., load demand, renewable
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. Develop intelligent algorithms that allow cooling systems to be controlled based on sensor inputs, ensuring adaptation to different scenarios and operating conditions; 4. Integrate and validate
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Artificial Intelligence models for the accurate simulation of motor racing and for the generation of suggestions for effective racing strategies. The research fellow will explore different modelling approaches
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learning algorithms, and design of optical communication networks or power consumption and energy saving. The synergies of MATCH consortium act together to enable the thirteen DCs to become the next
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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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methods supported in optimization and simulation, which will allow solving combinatorial problems and analysis of systems with different scales. In particular, the work plan includes the development and
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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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Instituto de Geografia e Ordenamento do Território da Universidade de Lisboa | Portugal | 16 days ago
for periodic reprocessing and extension to different regions; 2. Implement algorithms for the extraction and vectorisation of cartographic elements (e.g. administrative boundaries, transport networks, land use
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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